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filter</title> <meta name="description" content="Search results for: adaptive filter"> <meta name="keywords" content="adaptive filter"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button class="d-block d-lg-none navbar-toggler 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id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="adaptive filter"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 1820</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: adaptive filter</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1820</span> A New Sign Subband Adaptive Filter Based on Dynamic Selection of Subbands</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mohammad%20Shams%20Esfand%20Abadi">Mohammad Shams Esfand Abadi</a>, <a href="https://publications.waset.org/abstracts/search?q=Mehrdad%20Zalaghi"> Mehrdad Zalaghi</a>, <a href="https://publications.waset.org/abstracts/search?q=Reza%20ebrahimpour"> Reza ebrahimpour</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we propose a sign adaptive filter algorithm with the ability of dynamic selection of subband filters which leads to low computational complexity compared with conventional sign subband adaptive filter (SSAF) algorithm. Dynamic selection criterion is based on largest reduction of the mean square deviation at each adaption. We demonstrate that this simple proposed algorithm has the same performance of the conventional SSAF and somewhat faster than it. In the presence of impulsive interferences robustness of the simple proposed algorithm as well as the conventional SSAF and outperform the conventional normalized subband adaptive filter (NSAF) algorithm. Therefore, it is preferred for environments under impulsive interferences. Simulation results are presented to verify these above considerations very well have been achieved. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=acoustic%20echo%20cancellation%20%28AEC%29" title="acoustic echo cancellation (AEC)">acoustic echo cancellation (AEC)</a>, <a href="https://publications.waset.org/abstracts/search?q=normalized%20subband%20adaptive%20filter%20%28NSAF%29" title=" normalized subband adaptive filter (NSAF)"> normalized subband adaptive filter (NSAF)</a>, <a href="https://publications.waset.org/abstracts/search?q=dynamic%20selection%20subband%20adaptive%20filter%20%28DS-NSAF%29" title=" dynamic selection subband adaptive filter (DS-NSAF)"> dynamic selection subband adaptive filter (DS-NSAF)</a>, <a href="https://publications.waset.org/abstracts/search?q=sign%20subband%20adaptive%20filter%20%28SSAF%29" title=" sign subband adaptive filter (SSAF)"> sign subband adaptive filter (SSAF)</a>, <a href="https://publications.waset.org/abstracts/search?q=impulsive%20noise" title=" impulsive noise"> impulsive noise</a>, <a href="https://publications.waset.org/abstracts/search?q=robust%20filtering" title=" robust filtering"> robust filtering</a> </p> <a href="https://publications.waset.org/abstracts/20230/a-new-sign-subband-adaptive-filter-based-on-dynamic-selection-of-subbands" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/20230.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">599</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1819</span> Design of Reconfigurable Fixed-Point LMS Adaptive FIR Filter </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=S.%20Padmapriya">S. Padmapriya</a>, <a href="https://publications.waset.org/abstracts/search?q=V.%20Lakshmi%20Prabha"> V. Lakshmi Prabha</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, an efficient reconfigurable fixed-point Least Mean Square Adaptive FIR filter is proposed. The proposed architecture has two methods of operation: one is area efficient design and the other is optimized power. Pipelining of the adder blocks and partial product generator are used to achieve low area and reversible logic is used to obtain low power design. Depending upon the input samples and filter coefficients, one of the techniques is chosen. Least-Mean-Square adaptation is performed to update the weights. The architecture is coded using Verilog and synthesized in cadence encounter 0.18渭m technology. The synthesized results show that the area reduction ratio of the proposed when compared with conventional technique is about 1.2%. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=adaptive%20filter" title="adaptive filter">adaptive filter</a>, <a href="https://publications.waset.org/abstracts/search?q=carry%20select%20adder" title=" carry select adder"> carry select adder</a>, <a href="https://publications.waset.org/abstracts/search?q=least%20mean%20square%20algorithm" title=" least mean square algorithm"> least mean square algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=reversible%20logic" title=" reversible logic"> reversible logic</a> </p> <a href="https://publications.waset.org/abstracts/11853/design-of-reconfigurable-fixed-point-lms-adaptive-fir-filter" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/11853.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">330</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1818</span> Image Denoising Using Spatial Adaptive Mask Filter for Medical Images</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=R.%20Sumalatha">R. Sumalatha</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20V.%20Subramanyam"> M. V. Subramanyam</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In medical image processing the quality of the image is degraded in the presence of noise. Especially in ultra sound imaging and Magnetic resonance imaging the data was corrupted by signal dependent noise known as salt and pepper noise. Removal of noise from the medical images is a critical issue for researchers. In this paper, a new type of technique Adaptive Spatial Mask Filter (ASMF) has been proposed. The proposed filter is used to increase the quality of MRI and ultra sound images. Experimental results show that the proposed filter outperforms the implementation of mean, median, adaptive median filters in terms of MSE and PSNR. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=salt%20and%20pepper%20noise" title="salt and pepper noise">salt and pepper noise</a>, <a href="https://publications.waset.org/abstracts/search?q=ASMF" title=" ASMF"> ASMF</a>, <a href="https://publications.waset.org/abstracts/search?q=PSNR" title=" PSNR"> PSNR</a>, <a href="https://publications.waset.org/abstracts/search?q=MSE" title=" MSE"> MSE</a> </p> <a href="https://publications.waset.org/abstracts/3843/image-denoising-using-spatial-adaptive-mask-filter-for-medical-images" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/3843.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">435</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1817</span> Acoustic Echo Cancellation Using Different Adaptive Algorithms</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hamid%20Sharif">Hamid Sharif</a>, <a href="https://publications.waset.org/abstracts/search?q=Nazish%20Saleem%20Abbas"> Nazish Saleem Abbas</a>, <a href="https://publications.waset.org/abstracts/search?q=Muhammad%20Haris%20Jamil"> Muhammad Haris Jamil</a> </p> <p class="card-text"><strong>Abstract:</strong></p> An adaptive filter is a filter that self-adjusts its transfer function according to an optimization algorithm driven by an error signal. Because of the complexity of the optimization algorithms, most adaptive filters are digital filters. Adaptive filtering constitutes one of the core technologies in digital signal processing and finds numerous application areas in science as well as in industry. Adaptive filtering techniques are used in a wide range of applications, including adaptive noise cancellation and echo cancellation. Acoustic echo cancellation is a common occurrence in today鈥檚 telecommunication systems. The signal interference caused by acoustic echo is distracting to both users and causes a reduction in the quality of the communication. In this paper, we review different techniques of adaptive filtering to reduce this unwanted echo. In this paper, we see the behavior of techniques and algorithms of adaptive filtering like Least Mean Square (LMS), Normalized Least Mean Square (NLMS), Variable Step-Size Least Mean Square (VSLMS), Variable Step-Size Normalized Least Mean Square (VSNLMS), New Varying Step Size LMS Algorithm (NVSSLMS) and Recursive Least Square (RLS) algorithms to reduce this unwanted echo, to increase communication quality. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=adaptive%20acoustic" title="adaptive acoustic">adaptive acoustic</a>, <a href="https://publications.waset.org/abstracts/search?q=echo%20cancellation" title=" echo cancellation"> echo cancellation</a>, <a href="https://publications.waset.org/abstracts/search?q=LMS%20algorithm" title=" LMS algorithm"> LMS algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=adaptive%20filter" title=" adaptive filter"> adaptive filter</a>, <a href="https://publications.waset.org/abstracts/search?q=normalized%20least%20mean%20square%20%28NLMS%29" title=" normalized least mean square (NLMS)"> normalized least mean square (NLMS)</a>, <a href="https://publications.waset.org/abstracts/search?q=variable%20step-size%20least%20mean%20square%20%28VSLMS%29" title=" variable step-size least mean square (VSLMS)"> variable step-size least mean square (VSLMS)</a> </p> <a href="https://publications.waset.org/abstracts/167766/acoustic-echo-cancellation-using-different-adaptive-algorithms" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/167766.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">80</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1816</span> Design of Enhanced Adaptive Filter for Integrated Navigation System of FOG-SINS and Star Tracker</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nassim%20Bessaad">Nassim Bessaad</a>, <a href="https://publications.waset.org/abstracts/search?q=Qilian%20Bao"> Qilian Bao</a>, <a href="https://publications.waset.org/abstracts/search?q=Zhao%20Jiangkang"> Zhao Jiangkang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The fiber optics gyroscope in the strap-down inertial navigation system (FOG-SINS) suffers from precision degradation due to the influence of random errors. In this work, an enhanced Allan variance (AV) stochastic modeling method combined with discrete wavelet transform (DWT) for signal denoising is implemented to estimate the random process in the FOG signal. Furthermore, we devise a measurement-based iterative adaptive Sage-Husa nonlinear filter with augmented states to integrate a star tracker sensor with SINS. The proposed filter adapts the measurement noise covariance matrix based on the available data. Moreover, the enhanced stochastic modeling scheme is invested in tuning the process noise covariance matrix and the augmented state Gauss-Markov process parameters. Finally, the effectiveness of the proposed filter is investigated by employing the collected data in laboratory conditions. The result shows the filter's improved accuracy in comparison with the conventional Kalman filter (CKF). <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=inertial%20navigation" title="inertial navigation">inertial navigation</a>, <a href="https://publications.waset.org/abstracts/search?q=adaptive%20filtering" title=" adaptive filtering"> adaptive filtering</a>, <a href="https://publications.waset.org/abstracts/search?q=star%20tracker" title=" star tracker"> star tracker</a>, <a href="https://publications.waset.org/abstracts/search?q=FOG" title=" FOG"> FOG</a> </p> <a href="https://publications.waset.org/abstracts/145618/design-of-enhanced-adaptive-filter-for-integrated-navigation-system-of-fog-sins-and-star-tracker" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/145618.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">80</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1815</span> Application of Adaptive Particle Filter for Localizing a Mobile Robot Using 3D Camera Data</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Maysam%20Shahsavari">Maysam Shahsavari</a>, <a href="https://publications.waset.org/abstracts/search?q=Seyed%20Jamalaldin%20Haddadi"> Seyed Jamalaldin Haddadi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> There are several methods to localize a mobile robot such as relative, absolute and probabilistic. In this paper, particle filter due to its simple implementation and the fact that it does not need to know to the starting position will be used. This method estimates the position of the mobile robot using a probabilistic distribution, relying on a known map of the environment instead of predicting it. Afterwards, it updates this estimation by reading input sensors and control commands. To receive information from the surrounding world, distance to obstacles, for example, a Kinect is used which is much cheaper than a laser range finder. Finally, after explaining the Adaptive Particle Filter method and its implementation in detail, we will compare this method with the dead reckoning method and show that this method is much more suitable for situations in which we have a map of the environment. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=particle%20filter" title="particle filter">particle filter</a>, <a href="https://publications.waset.org/abstracts/search?q=localization" title=" localization"> localization</a>, <a href="https://publications.waset.org/abstracts/search?q=methods" title=" methods"> methods</a>, <a href="https://publications.waset.org/abstracts/search?q=odometry" title=" odometry"> odometry</a>, <a href="https://publications.waset.org/abstracts/search?q=kinect" title=" kinect "> kinect </a> </p> <a href="https://publications.waset.org/abstracts/53041/application-of-adaptive-particle-filter-for-localizing-a-mobile-robot-using-3d-camera-data" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/53041.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">269</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1814</span> Adaptive Filtering in Subbands for Supervised Source Separation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Bruna%20Luisa%20Ramos%20Prado%20Vasques">Bruna Luisa Ramos Prado Vasques</a>, <a href="https://publications.waset.org/abstracts/search?q=Mariane%20Rembold%20Petraglia"> Mariane Rembold Petraglia</a>, <a href="https://publications.waset.org/abstracts/search?q=Antonio%20Petraglia"> Antonio Petraglia</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper investigates MIMO (Multiple-Input Multiple-Output) adaptive filtering techniques for the application of supervised source separation in the context of convolutive mixtures. From the observation that there is correlation among the signals of the different mixtures, an improvement in the NSAF (Normalized Subband Adaptive Filter) algorithm is proposed in order to accelerate its convergence rate. Simulation results with mixtures of speech signals in reverberant environments show the superior performance of the proposed algorithm with respect to the performances of the NLMS (Normalized Least-Mean-Square) and conventional NSAF, considering both the convergence speed and SIR (Signal-to-Interference Ratio) after convergence. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=adaptive%20filtering" title="adaptive filtering">adaptive filtering</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-rate%20processing" title=" multi-rate processing"> multi-rate processing</a>, <a href="https://publications.waset.org/abstracts/search?q=normalized%20subband%20adaptive%20filter" title=" normalized subband adaptive filter"> normalized subband adaptive filter</a>, <a href="https://publications.waset.org/abstracts/search?q=source%20separation" title=" source separation"> source separation</a> </p> <a href="https://publications.waset.org/abstracts/78300/adaptive-filtering-in-subbands-for-supervised-source-separation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/78300.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">435</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1813</span> An Efficient Separation for Convolutive Mixtures</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Salah%20Al-Din%20I.%20Badran">Salah Al-Din I. Badran</a>, <a href="https://publications.waset.org/abstracts/search?q=Samad%20Ahmadi"> Samad Ahmadi</a>, <a href="https://publications.waset.org/abstracts/search?q=Dylan%20Menzies"> Dylan Menzies</a>, <a href="https://publications.waset.org/abstracts/search?q=Ismail%20Shahin"> Ismail Shahin</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper describes a new efficient blind source separation method; in this method we use a non-uniform filter bank and a new structure with different sub-bands. This method provides a reduced permutation and increased convergence speed comparing to the full-band algorithm. Recently, some structures have been suggested to deal with two problems: reducing permutation and increasing the speed of convergence of the adaptive algorithm for correlated input signals. The permutation problem is avoided with the use of adaptive filters of orders less than the full-band adaptive filter, which operate at a sampling rate lower than the sampling rate of the input signal. The decomposed signals by analysis bank filter are less correlated in each sub-band than the input signal at full-band, and can promote better rates of convergence. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Blind%20source%20separation" title="Blind source separation">Blind source separation</a>, <a href="https://publications.waset.org/abstracts/search?q=estimates" title=" estimates"> estimates</a>, <a href="https://publications.waset.org/abstracts/search?q=full-band" title=" full-band"> full-band</a>, <a href="https://publications.waset.org/abstracts/search?q=mixtures" title=" mixtures"> mixtures</a>, <a href="https://publications.waset.org/abstracts/search?q=sub-band" title=" sub-band"> sub-band</a> </p> <a href="https://publications.waset.org/abstracts/8254/an-efficient-separation-for-convolutive-mixtures" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/8254.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">444</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1812</span> Phasor Measurement Unit Based on Particle Filtering</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rithvik%20Reddy%20Adapa">Rithvik Reddy Adapa</a>, <a href="https://publications.waset.org/abstracts/search?q=Xin%20Wang"> Xin Wang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Phasor Measurement Units (PMUs) are very sophisticated measuring devices that find amplitude, phase and frequency of various voltages and currents in a power system. Particle filter is a state estimation technique that uses Bayesian inference. Particle filters are widely used in pose estimation and indoor navigation and are very reliable. This paper studies and compares four different particle filters as PMUs namely, generic particle filter (GPF), genetic algorithm particle filter (GAPF), particle swarm optimization particle filter (PSOPF) and adaptive particle filter (APF). Two different test signals are used to test the performance of the filters in terms of responsiveness and correctness of the estimates. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=phasor%20measurement%20unit" title="phasor measurement unit">phasor measurement unit</a>, <a href="https://publications.waset.org/abstracts/search?q=particle%20filter" title=" particle filter"> particle filter</a>, <a href="https://publications.waset.org/abstracts/search?q=genetic%20algorithm" title=" genetic algorithm"> genetic algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=particle%20swarm%20optimisation" title=" particle swarm optimisation"> particle swarm optimisation</a>, <a href="https://publications.waset.org/abstracts/search?q=state%20estimation" title=" state estimation"> state estimation</a> </p> <a href="https://publications.waset.org/abstracts/194127/phasor-measurement-unit-based-on-particle-filtering" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/194127.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">8</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1811</span> Adaptive Kaman Filter for Fault Diagnosis of Linear Parameter-Varying Systems</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rajamani%20Doraiswami">Rajamani Doraiswami</a>, <a href="https://publications.waset.org/abstracts/search?q=Lahouari%20Cheded"> Lahouari Cheded</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Fault diagnosis of Linear Parameter-Varying (LPV) system using an adaptive Kalman filter is proposed. The LPV model is comprised of scheduling parameters, and the emulator parameters. The scheduling parameters are chosen such that they are capable of tracking variations in the system model as a result of changes in the operating regimes. The emulator parameters, on the other hand, simulate variations in the subsystems during the identification phase and have negligible effect during the operational phase. The nominal model and the influence vectors, which are the gradient of the feature vector respect to the emulator parameters, are identified off-line from a number of emulator parameter perturbed experiments. A Kalman filter is designed using the identified nominal model. As the system varies, the Kalman filter model is adapted using the scheduling variables. The residual is employed for fault diagnosis. The proposed scheme is successfully evaluated on simulated system as well as on a physical process control system. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=identification" title="identification">identification</a>, <a href="https://publications.waset.org/abstracts/search?q=linear%20parameter-varying%20systems" title=" linear parameter-varying systems"> linear parameter-varying systems</a>, <a href="https://publications.waset.org/abstracts/search?q=least-squares%20estimation" title=" least-squares estimation"> least-squares estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=fault%20diagnosis" title=" fault diagnosis"> fault diagnosis</a>, <a href="https://publications.waset.org/abstracts/search?q=Kalman%20filter" title=" Kalman filter"> Kalman filter</a>, <a href="https://publications.waset.org/abstracts/search?q=emulators" title=" emulators"> emulators</a> </p> <a href="https://publications.waset.org/abstracts/7656/adaptive-kaman-filter-for-fault-diagnosis-of-linear-parameter-varying-systems" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/7656.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">499</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1810</span> A Novel RLS Based Adaptive Filtering Method for Speech Enhancement</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Pogula%20Rakesh">Pogula Rakesh</a>, <a href="https://publications.waset.org/abstracts/search?q=T.%20Kishore%20Kumar"> T. Kishore Kumar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Speech enhancement is a long standing problem with numerous applications like teleconferencing, VoIP, hearing aids, and speech recognition. The motivation behind this research work is to obtain a clean speech signal of higher quality by applying the optimal noise cancellation technique. Real-time adaptive filtering algorithms seem to be the best candidate among all categories of the speech enhancement methods. In this paper, we propose a speech enhancement method based on Recursive Least Squares (RLS) adaptive filter of speech signals. Experiments were performed on noisy data which was prepared by adding AWGN, Babble and Pink noise to clean speech samples at -5dB, 0dB, 5dB, and 10dB SNR levels. We then compare the noise cancellation performance of proposed RLS algorithm with existing NLMS algorithm in terms of Mean Squared Error (MSE), Signal to Noise ratio (SNR), and SNR loss. Based on the performance evaluation, the proposed RLS algorithm was found to be a better optimal noise cancellation technique for speech signals. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=adaptive%20filter" title="adaptive filter">adaptive filter</a>, <a href="https://publications.waset.org/abstracts/search?q=adaptive%20noise%20canceller" title=" adaptive noise canceller"> adaptive noise canceller</a>, <a href="https://publications.waset.org/abstracts/search?q=mean%20squared%20error" title=" mean squared error"> mean squared error</a>, <a href="https://publications.waset.org/abstracts/search?q=noise%20reduction" title=" noise reduction"> noise reduction</a>, <a href="https://publications.waset.org/abstracts/search?q=NLMS" title=" NLMS"> NLMS</a>, <a href="https://publications.waset.org/abstracts/search?q=RLS" title=" RLS"> RLS</a>, <a href="https://publications.waset.org/abstracts/search?q=SNR" title=" SNR"> SNR</a>, <a href="https://publications.waset.org/abstracts/search?q=SNR%20loss" title=" SNR loss"> SNR loss</a> </p> <a href="https://publications.waset.org/abstracts/16212/a-novel-rls-based-adaptive-filtering-method-for-speech-enhancement" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/16212.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">481</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1809</span> A Fast Convergence Subband BSS Structure</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Salah%20Al-Din%20I.%20Badran">Salah Al-Din I. Badran</a>, <a href="https://publications.waset.org/abstracts/search?q=Samad%20Ahmadi"> Samad Ahmadi</a>, <a href="https://publications.waset.org/abstracts/search?q=Ismail%20Shahin"> Ismail Shahin</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A blind source separation method is proposed; in this method we use a non-uniform filter bank and a novel normalisation. This method provides a reduced computational complexity and increased convergence speed comparing to the full-band algorithm. Recently, adaptive sub-band scheme has been recommended to solve two problems: reduction of computational complexity and increase the convergence speed of the adaptive algorithm for correlated input signals. In this work the reduction in computational complexity is achieved with the use of adaptive filters of orders less than the full-band adaptive filters, which operate at a sampling rate lower than the sampling rate of the input signal. The decomposed signals by analysis bank filter are less correlated in each sub-band than the input signal at full bandwidth, and can promote better rates of convergence. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=blind%20source%20separation" title="blind source separation">blind source separation</a>, <a href="https://publications.waset.org/abstracts/search?q=computational%20complexity" title=" computational complexity"> computational complexity</a>, <a href="https://publications.waset.org/abstracts/search?q=subband" title=" subband"> subband</a>, <a href="https://publications.waset.org/abstracts/search?q=convergence%20speed" title=" convergence speed"> convergence speed</a>, <a href="https://publications.waset.org/abstracts/search?q=mixture" title=" mixture"> mixture</a> </p> <a href="https://publications.waset.org/abstracts/33150/a-fast-convergence-subband-bss-structure" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/33150.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">555</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1808</span> A Subband BSS Structure with Reduced Complexity and Fast Convergence</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Salah%20Al-Din%20I.%20Badran">Salah Al-Din I. Badran</a>, <a href="https://publications.waset.org/abstracts/search?q=Samad%20Ahmadi"> Samad Ahmadi</a>, <a href="https://publications.waset.org/abstracts/search?q=Ismail%20Shahin"> Ismail Shahin</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A blind source separation method is proposed; in this method, we use a non-uniform filter bank and a novel normalisation. This method provides a reduced computational complexity and increased convergence speed comparing to the full-band algorithm. Recently, adaptive sub-band scheme has been recommended to solve two problems: reduction of computational complexity and increase the convergence speed of the adaptive algorithm for correlated input signals. In this work, the reduction in computational complexity is achieved with the use of adaptive filters of orders less than the full-band adaptive filters, which operate at a sampling rate lower than the sampling rate of the input signal. The decomposed signals by analysis bank filter are less correlated in each subband than the input signal at full bandwidth, and can promote better rates of convergence. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=blind%20source%20separation" title="blind source separation">blind source separation</a>, <a href="https://publications.waset.org/abstracts/search?q=computational%20complexity" title=" computational complexity"> computational complexity</a>, <a href="https://publications.waset.org/abstracts/search?q=subband" title=" subband"> subband</a>, <a href="https://publications.waset.org/abstracts/search?q=convergence%20speed" title=" convergence speed"> convergence speed</a>, <a href="https://publications.waset.org/abstracts/search?q=mixture" title=" mixture "> mixture </a> </p> <a href="https://publications.waset.org/abstracts/33346/a-subband-bss-structure-with-reduced-complexity-and-fast-convergence" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/33346.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">579</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1807</span> An Overview of Adaptive Channel Equalization Techniques and Algorithms</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Navdeep%20Singh%20Randhawa">Navdeep Singh Randhawa</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Wireless communication system has been proved as the best for any communication. However, there are some undesirable threats of a wireless communication channel on the information transmitted through it, such as attenuation, distortions, delays and phase shifts of the signals arriving at the receiver end which are caused by its band limited and dispersive nature. One of the threat is ISI (Inter Symbol Interference), which has been found as a great obstacle in high speed communication. Thus, there is a need to provide perfect and accurate technique to remove this effect to have an error free communication. Thus, different equalization techniques have been proposed in literature. This paper presents the equalization techniques followed by the concept of adaptive filter equalizer, its algorithms (LMS and RLS) and applications of adaptive equalization technique. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=channel%20equalization" title="channel equalization">channel equalization</a>, <a href="https://publications.waset.org/abstracts/search?q=adaptive%20equalizer" title=" adaptive equalizer"> adaptive equalizer</a>, <a href="https://publications.waset.org/abstracts/search?q=least%20mean%20square" title=" least mean square"> least mean square</a>, <a href="https://publications.waset.org/abstracts/search?q=recursive%20least%20square" title=" recursive least square"> recursive least square</a> </p> <a href="https://publications.waset.org/abstracts/9270/an-overview-of-adaptive-channel-equalization-techniques-and-algorithms" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/9270.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">450</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1806</span> Gaussian Particle Flow Bernoulli Filter for Single Target Tracking</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hyeongbok%20Kim">Hyeongbok Kim</a>, <a href="https://publications.waset.org/abstracts/search?q=Lingling%20Zhao"> Lingling Zhao</a>, <a href="https://publications.waset.org/abstracts/search?q=Xiaohong%20Su"> Xiaohong Su</a>, <a href="https://publications.waset.org/abstracts/search?q=Junjie%20Wang"> Junjie Wang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The Bernoulli filter is a precise Bayesian filter for single target tracking based on the random finite set theory. The standard Bernoulli filter often underestimates the number of targets. This study proposes a Gaussian particle flow (GPF) Bernoulli filter employing particle flow to migrate particles from prior to posterior positions to improve the performance of the standard Bernoulli filter. By employing the particle flow filter, the computational speed of the Bernoulli filters is significantly improved. In addition, the GPF Bernoulli filter provides a more accurate estimation compared with that of the standard Bernoulli filter. Simulation results confirm the improved tracking performance and computational speed in two- and three-dimensional scenarios compared with other algorithms. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Bernoulli%20filter" title="Bernoulli filter">Bernoulli filter</a>, <a href="https://publications.waset.org/abstracts/search?q=particle%20filter" title=" particle filter"> particle filter</a>, <a href="https://publications.waset.org/abstracts/search?q=particle%20flow%20filter" title=" particle flow filter"> particle flow filter</a>, <a href="https://publications.waset.org/abstracts/search?q=random%20finite%20sets" title=" random finite sets"> random finite sets</a>, <a href="https://publications.waset.org/abstracts/search?q=target%20tracking" title=" target tracking"> target tracking</a> </p> <a href="https://publications.waset.org/abstracts/162210/gaussian-particle-flow-bernoulli-filter-for-single-target-tracking" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/162210.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">92</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1805</span> Kalman Filter Gain Elimination in Linear Estimation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nicholas%20D.%20Assimakis">Nicholas D. Assimakis</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In linear estimation, the traditional Kalman filter uses the Kalman filter gain in order to produce estimation and prediction of the n-dimensional state vector using the m-dimensional measurement vector. The computation of the Kalman filter gain requires the inversion of an m x m matrix in every iteration. In this paper, a variation of the Kalman filter eliminating the Kalman filter gain is proposed. In the time varying case, the elimination of the Kalman filter gain requires the inversion of an n x n matrix and the inversion of an m x m matrix in every iteration. In the time invariant case, the elimination of the Kalman filter gain requires the inversion of an n x n matrix in every iteration. The proposed Kalman filter gain elimination algorithm may be faster than the conventional Kalman filter, depending on the model dimensions. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=discrete%20time" title="discrete time">discrete time</a>, <a href="https://publications.waset.org/abstracts/search?q=estimation" title=" estimation"> estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=Kalman%20filter" title=" Kalman filter"> Kalman filter</a>, <a href="https://publications.waset.org/abstracts/search?q=Kalman%20filter%20gain" title=" Kalman filter gain"> Kalman filter gain</a> </p> <a href="https://publications.waset.org/abstracts/123040/kalman-filter-gain-elimination-in-linear-estimation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/123040.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">195</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1804</span> Study of Adaptive Filtering Algorithms and the Equalization of Radio Mobile Channel</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Said%20Elkassimi">Said Elkassimi</a>, <a href="https://publications.waset.org/abstracts/search?q=Said%20Safi"> Said Safi</a>, <a href="https://publications.waset.org/abstracts/search?q=B.%20Manaut"> B. Manaut</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presented a study of three algorithms, the equalization algorithm to equalize the transmission channel with ZF and MMSE criteria, application of channel Bran A, and adaptive filtering algorithms LMS and RLS to estimate the parameters of the equalizer filter, i.e. move to the channel estimation and therefore reflect the temporal variations of the channel, and reduce the error in the transmitted signal. So far the performance of the algorithm equalizer with ZF and MMSE criteria both in the case without noise, a comparison of performance of the LMS and RLS algorithm. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=adaptive%20filtering%20second%20equalizer" title="adaptive filtering second equalizer">adaptive filtering second equalizer</a>, <a href="https://publications.waset.org/abstracts/search?q=LMS" title=" LMS"> LMS</a>, <a href="https://publications.waset.org/abstracts/search?q=RLS%20%20Bran%20A" title=" RLS Bran A"> RLS Bran A</a>, <a href="https://publications.waset.org/abstracts/search?q=Proakis%20%28B%29%20MMSE" title=" Proakis (B) MMSE"> Proakis (B) MMSE</a>, <a href="https://publications.waset.org/abstracts/search?q=ZF" title=" ZF"> ZF</a> </p> <a href="https://publications.waset.org/abstracts/32853/study-of-adaptive-filtering-algorithms-and-the-equalization-of-radio-mobile-channel" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/32853.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">313</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1803</span> Operation Parameters of Vacuum Cleaned Filters</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Wilhelm%20Hoeflinger">Wilhelm Hoeflinger</a>, <a href="https://publications.waset.org/abstracts/search?q=Thomas%20Laminger"> Thomas Laminger</a>, <a href="https://publications.waset.org/abstracts/search?q=Johannes%20Wolfslehner"> Johannes Wolfslehner</a> </p> <p class="card-text"><strong>Abstract:</strong></p> For vacuum cleaned dust filters, used e. g. in textile industry, there exist no calculation methods to determine design parameters (e. g. traverse speed of the nozzle, filter area...). In this work a method to calculate the optimum traverse speed of the nozzle of an industrial-size flat dust filter at a given mean pressure drop and filter face velocity was elaborated. Well-known equations for the design of a cleanable multi-chamber bag-house-filter were modified in order to take into account a continuously regeneration of a dust filter by a nozzle. Thereby, the specific filter medium resistance and the specific cake resistance values are needed which can be derived from filter tests under constant operation conditions. A lab-scale filter test rig was used to derive the specific filter media resistance value and the specific cake resistance value for vacuum cleaned filter operation. Three different filter media were tested and the determined parameters were compared to each other. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=design%20of%20dust%20filter" title="design of dust filter">design of dust filter</a>, <a href="https://publications.waset.org/abstracts/search?q=dust%20removing" title=" dust removing"> dust removing</a>, <a href="https://publications.waset.org/abstracts/search?q=filter%20regeneration" title=" filter regeneration"> filter regeneration</a>, <a href="https://publications.waset.org/abstracts/search?q=operation%20parameters" title=" operation parameters"> operation parameters</a> </p> <a href="https://publications.waset.org/abstracts/2536/operation-parameters-of-vacuum-cleaned-filters" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/2536.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">387</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1802</span> Compact Microstrip Ultra-Wideband Bandstop Filter With Quasi-Elliptic Function Response</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hussein%20Shaman">Hussein Shaman</a>, <a href="https://publications.waset.org/abstracts/search?q=Faris%20Almansour"> Faris Almansour</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper proposes a modified optimum bandstop filter with ultra-wideband stopband. The filter consists of three shunt open-circuited stubs and two non-redundant unit elements. The proposed bandstop filter is designed with unequal electrical lengths of the open-circuited stubs at the mid-stopband. Therefore, the filter can exhibit a quasi-elliptic function response that improves the selectivity and enhances the rejection bandwidth. The filter is designed to exhibit a fractional bandwidth of about 114% at a mid-stopband frequency of 3.0 GHz. The filter is successfully realized in theory, simulated, fabricated and measured. An excellent agreement is obtained between calculated, simulated and measured. The fabricated filter has a compact size with a low insertion loss in the passbands, high selectivity and good attenuation level inside the desired stopband <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=microstrip%20filter" title="microstrip filter">microstrip filter</a>, <a href="https://publications.waset.org/abstracts/search?q=bandstop%20filter" title=" bandstop filter"> bandstop filter</a>, <a href="https://publications.waset.org/abstracts/search?q=UWB%20filter" title=" UWB filter"> UWB filter</a>, <a href="https://publications.waset.org/abstracts/search?q=transmission%20line%20filter" title=" transmission line filter"> transmission line filter</a> </p> <a href="https://publications.waset.org/abstracts/151305/compact-microstrip-ultra-wideband-bandstop-filter-with-quasi-elliptic-function-response" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/151305.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">148</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1801</span> Identifying the Gap between Adaptive Clothing Consumers and Brands</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Lucky%20Farha">Lucky Farha</a>, <a href="https://publications.waset.org/abstracts/search?q=Martha%20L.%20Hall"> Martha L. Hall</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The current adaptive clothing brands are limited in numbers and specific categories. This study explores clothing challenges for children with Down syndrome and factors that influence their perception of adaptive clothing brands. Another aim of this study was to explore brands' challenges in the adaptive business and factors that influence their perceptions towards the adaptive market. In order to determine the market barriers affecting adaptive target market needs, the researcher applied Technology Acceptance Model. After interviewing and surveying parents/caregivers having children with Down syndrome and current adaptive brands, the results found education as the significant gap in the adaptive clothing market yet to be overcome. Based on the finding, several recommendations were suggested to improve the current barriers in the adaptive clothing market. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=adaptive%20fashion" title="adaptive fashion">adaptive fashion</a>, <a href="https://publications.waset.org/abstracts/search?q=disability" title=" disability"> disability</a>, <a href="https://publications.waset.org/abstracts/search?q=functional%20clothing" title=" functional clothing"> functional clothing</a>, <a href="https://publications.waset.org/abstracts/search?q=clothing%20needs%20assessment" title=" clothing needs assessment"> clothing needs assessment</a>, <a href="https://publications.waset.org/abstracts/search?q=down%20syndrome" title=" down syndrome"> down syndrome</a>, <a href="https://publications.waset.org/abstracts/search?q=clothing%20challenge" title=" clothing challenge"> clothing challenge</a> </p> <a href="https://publications.waset.org/abstracts/150986/identifying-the-gap-between-adaptive-clothing-consumers-and-brands" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/150986.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">143</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1800</span> An Adaptive Back-Propagation Network and Kalman Filter Based Multi-Sensor Fusion Method for Train Location System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yu-ding%20Du">Yu-ding Du</a>, <a href="https://publications.waset.org/abstracts/search?q=Qi-lian%20Bao"> Qi-lian Bao</a>, <a href="https://publications.waset.org/abstracts/search?q=Nassim%20Bessaad"> Nassim Bessaad</a>, <a href="https://publications.waset.org/abstracts/search?q=Lin%20Liu"> Lin Liu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The Global Navigation Satellite System (GNSS) is regarded as an effective approach for the purpose of replacing the large amount used track-side balises in modern train localization systems. This paper describes a method based on the data fusion of a GNSS receiver sensor and an odometer sensor that can significantly improve the positioning accuracy. A digital track map is needed as another sensor to project two-dimensional GNSS position to one-dimensional along-track distance due to the fact that the train鈥檚 position can only be constrained on the track. A model trained by BP neural network is used to estimate the trend positioning error which is related to the specific location and proximate processing of the digital track map. Considering that in some conditions the satellite signal failure will lead to the increase of GNSS positioning error, a detection step for GNSS signal is applied. An adaptive weighted fusion algorithm is presented to reduce the standard deviation of train speed measurement. Finally an Extended Kalman Filter (EKF) is used for the fusion of the projected 1-D GNSS positioning data and the 1-D train speed data to get the estimate position. Experimental results suggest that the proposed method performs well, which can reduce positioning error notably. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=multi-sensor%20data%20fusion" title="multi-sensor data fusion">multi-sensor data fusion</a>, <a href="https://publications.waset.org/abstracts/search?q=train%20positioning" title=" train positioning"> train positioning</a>, <a href="https://publications.waset.org/abstracts/search?q=GNSS" title=" GNSS"> GNSS</a>, <a href="https://publications.waset.org/abstracts/search?q=odometer" title=" odometer"> odometer</a>, <a href="https://publications.waset.org/abstracts/search?q=digital%20track%20map" title=" digital track map"> digital track map</a>, <a href="https://publications.waset.org/abstracts/search?q=map%20matching" title=" map matching"> map matching</a>, <a href="https://publications.waset.org/abstracts/search?q=BP%20neural%20network" title=" BP neural network"> BP neural network</a>, <a href="https://publications.waset.org/abstracts/search?q=adaptive%20weighted%20fusion" title=" adaptive weighted fusion"> adaptive weighted fusion</a>, <a href="https://publications.waset.org/abstracts/search?q=Kalman%20filter" title=" Kalman filter"> Kalman filter</a> </p> <a href="https://publications.waset.org/abstracts/98264/an-adaptive-back-propagation-network-and-kalman-filter-based-multi-sensor-fusion-method-for-train-location-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/98264.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">252</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1799</span> A Finite Memory Residual Generation Filter for Fault Detection</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Pyung%20Soo%20Kim">Pyung Soo Kim</a>, <a href="https://publications.waset.org/abstracts/search?q=Eung%20Hyuk%20Lee"> Eung Hyuk Lee</a>, <a href="https://publications.waset.org/abstracts/search?q=Mun%20Suck%20Jang"> Mun Suck Jang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In the current paper, a residual generation filter with finite memory structure is proposed for fault detection. The proposed finite memory residual generation filter provides the residual by real-time filtering of fault vector using only the most recent finite observations and inputs on the window. It is shown that the residual given by the proposed residual generation filter provides the exact fault for noise-free systems. Finally, to illustrate the capability of the proposed residual generation filter, numerical examples are performed for the discretized DC motor system having the multiple sensor faults. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=residual%20generation%20filter" title="residual generation filter">residual generation filter</a>, <a href="https://publications.waset.org/abstracts/search?q=finite%20memory%20structure" title=" finite memory structure"> finite memory structure</a>, <a href="https://publications.waset.org/abstracts/search?q=kalman%20filter" title=" kalman filter"> kalman filter</a>, <a href="https://publications.waset.org/abstracts/search?q=fast%20detection" title=" fast detection"> fast detection</a> </p> <a href="https://publications.waset.org/abstracts/35140/a-finite-memory-residual-generation-filter-for-fault-detection" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/35140.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">698</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1798</span> Real-Time Classification of Hemodynamic Response by Functional Near-Infrared Spectroscopy Using an Adaptive Estimation of General Linear Model Coefficients</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sahar%20Jahani">Sahar Jahani</a>, <a href="https://publications.waset.org/abstracts/search?q=Meryem%20Ayse%20Yucel"> Meryem Ayse Yucel</a>, <a href="https://publications.waset.org/abstracts/search?q=David%20Boas"> David Boas</a>, <a href="https://publications.waset.org/abstracts/search?q=Seyed%20Kamaledin%20Setarehdan"> Seyed Kamaledin Setarehdan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Near-infrared spectroscopy allows monitoring of oxy- and deoxy-hemoglobin concentration changes associated with hemodynamic response function (HRF). HRF is usually affected by natural physiological hemodynamic (systemic interferences) which occur in all body tissues including brain tissue. This makes HRF extraction a very challenging task. In this study, we used Kalman filter based on a general linear model (GLM) of brain activity to define the proportion of systemic interference in the brain hemodynamic. The performance of the proposed algorithm is evaluated in terms of the peak to peak error (Ep), mean square error (MSE), and Pearson鈥檚 correlation coefficient (R2) criteria between the estimated and the simulated hemodynamic responses. This technique also has the ability of real time estimation of single trial functional activations as it was applied to classify finger tapping versus resting state. The average real-time classification accuracy of 74% over 11 subjects demonstrates the feasibility of developing an effective functional near infrared spectroscopy for brain computer interface purposes (fNIRS-BCI). <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=hemodynamic%20response%20function" title="hemodynamic response function">hemodynamic response function</a>, <a href="https://publications.waset.org/abstracts/search?q=functional%20near-infrared%20spectroscopy" title=" functional near-infrared spectroscopy"> functional near-infrared spectroscopy</a>, <a href="https://publications.waset.org/abstracts/search?q=adaptive%20filter" title=" adaptive filter"> adaptive filter</a>, <a href="https://publications.waset.org/abstracts/search?q=Kalman%20filter" title=" Kalman filter"> Kalman filter</a> </p> <a href="https://publications.waset.org/abstracts/91765/real-time-classification-of-hemodynamic-response-by-functional-near-infrared-spectroscopy-using-an-adaptive-estimation-of-general-linear-model-coefficients" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/91765.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">164</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1797</span> Computational Cell Segmentation in Immunohistochemically Image of Meningioma Tumor Using Fuzzy C-Means and Adaptive Vector Directional Filter</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Vahid%20Anari">Vahid Anari</a>, <a href="https://publications.waset.org/abstracts/search?q=Leila%20Shahmohammadi"> Leila Shahmohammadi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Diagnosing and interpreting manually from a large cohort dataset of immunohistochemically stained tissue of tumors using an optical microscope involves subjectivity and also is tedious for pathologist specialists. Moreover, digital pathology today represents more of an evolution than a revolution in pathology. In this paper, we develop and test an unsupervised algorithm that can automatically enhance the IHC image of a meningioma tumor and classify cells into positive (proliferative) and negative (normal) cells. A dataset including 150 images is used to test the scheme. In addition, a new adaptive color image enhancement method is proposed based on a vector directional filter (VDF) and statistical properties of filtering the window. Since the cells are distinguishable by the human eye, the accuracy and stability of the algorithm are quantitatively compared through application to a wide variety of real images. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=digital%20pathology" title="digital pathology">digital pathology</a>, <a href="https://publications.waset.org/abstracts/search?q=cell%20segmentation" title=" cell segmentation"> cell segmentation</a>, <a href="https://publications.waset.org/abstracts/search?q=immunohistochemically" title=" immunohistochemically"> immunohistochemically</a>, <a href="https://publications.waset.org/abstracts/search?q=noise%20reduction" title=" noise reduction"> noise reduction</a> </p> <a href="https://publications.waset.org/abstracts/166868/computational-cell-segmentation-in-immunohistochemically-image-of-meningioma-tumor-using-fuzzy-c-means-and-adaptive-vector-directional-filter" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/166868.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">67</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1796</span> Study on Filter for Semiconductor of Minimizing Damage by X-Ray Laminography</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Chan%20Jong%20Park">Chan Jong Park</a>, <a href="https://publications.waset.org/abstracts/search?q=Hye%20Min%20Park"> Hye Min Park</a>, <a href="https://publications.waset.org/abstracts/search?q=Jeong%20Ho%20Kim"> Jeong Ho Kim</a>, <a href="https://publications.waset.org/abstracts/search?q=Ki%20Hyun%20Park"> Ki Hyun Park</a>, <a href="https://publications.waset.org/abstracts/search?q=Koan%20Sik%20Joo"> Koan Sik Joo</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This research used the MCNPX simulation program to evaluate the utility of a filter that was developed to minimize the damage to a semiconductor device during defect testing with X-ray. The X-ray generator was designed using the MCNPX code, and the X-ray absorption spectrum of the semiconductor device was obtained based on the designed X-ray generator code. To evaluate the utility of the filter, the X-ray absorption rates of the semiconductor device were calculated and compared for Ag, Rh, Mo and V filters with thicknesses of 25渭m, 50渭m, and 75渭m. The results showed that the X-ray absorption rate varied with the type and thickness of the filter, ranging from 8.74% to 49.28%. The Rh filter showed the highest X-ray absorption rates of 29.8%, 15.18% and 8.74% for the above-mentioned filter thicknesses. As shown above, the characteristics of the X-ray absorption with respect to the type and thickness of the filter were identified using MCNPX simulation. With these results, both time and expense could be saved in the production of the desired filter. In the future, this filter will be produced, and its performance will be evaluated. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=X-ray" title="X-ray">X-ray</a>, <a href="https://publications.waset.org/abstracts/search?q=MCNPX" title=" MCNPX"> MCNPX</a>, <a href="https://publications.waset.org/abstracts/search?q=filter" title=" filter"> filter</a>, <a href="https://publications.waset.org/abstracts/search?q=semiconductor" title=" semiconductor"> semiconductor</a>, <a href="https://publications.waset.org/abstracts/search?q=damage" title=" damage"> damage</a> </p> <a href="https://publications.waset.org/abstracts/53350/study-on-filter-for-semiconductor-of-minimizing-damage-by-x-ray-laminography" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/53350.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">423</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1795</span> Vibration Control of a Flexible Structure Using MFC Actuator</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jinsiang%20Shaw">Jinsiang Shaw</a>, <a href="https://publications.waset.org/abstracts/search?q=Jeng-Jie%20Huang"> Jeng-Jie Huang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Active vibration control is good for low frequency excitation, with advantages of light weight and adaptability. This paper employs a macro-fiber composite (MFC) actuator for vibration suppression in a cantilevered beam due to its higher output force to reject the disturbance. A notch filter with an adaptive tuning algorithm, the leaky filtered-X least mean square algorithm (leaky FXLMS algorithm), is developed and applied to the system. Experimental results show that the controller and MFC actuator was very effective in attenuating the structural vibration. Furthermore, this notch filter controller was compared with the traditional skyhook controller. It was found that its performance was better, with over 88% vibration suppression near the first resonant frequency of the structure. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=macro-fiber%20composite" title="macro-fiber composite">macro-fiber composite</a>, <a href="https://publications.waset.org/abstracts/search?q=notch%20filter" title=" notch filter"> notch filter</a>, <a href="https://publications.waset.org/abstracts/search?q=skyhook%20controller" title=" skyhook controller"> skyhook controller</a>, <a href="https://publications.waset.org/abstracts/search?q=vibration%20suppression" title=" vibration suppression"> vibration suppression</a> </p> <a href="https://publications.waset.org/abstracts/7710/vibration-control-of-a-flexible-structure-using-mfc-actuator" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/7710.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">462</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1794</span> A Packet Loss Probability Estimation Filter Using Most Recent Finite Traffic Measurements</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Pyung%20Soo%20Kim">Pyung Soo Kim</a>, <a href="https://publications.waset.org/abstracts/search?q=Eung%20Hyuk%20Lee"> Eung Hyuk Lee</a>, <a href="https://publications.waset.org/abstracts/search?q=Mun%20Suck%20Jang"> Mun Suck Jang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A packet loss probability (PLP) estimation filter with finite memory structure is proposed to estimate the packet rate mean and variance of the input traffic process in real-time while removing undesired system and measurement noises. The proposed PLP estimation filter is developed under a weighted least square criterion using only the finite traffic measurements on the most recent window. The proposed PLP estimation filter is shown to have several inherent properties such as unbiasedness, deadbeat, robustness. A guideline for choosing appropriate window length is described since it can affect significantly the estimation performance. Using computer simulations, the proposed PLP estimation filter is shown to be superior to the Kalman filter for the temporarily uncertain system. One possible explanation for this is that the proposed PLP estimation filter can have greater convergence time of a filtered estimate as the window length M decreases. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=packet%20loss%20probability%20estimation" title="packet loss probability estimation">packet loss probability estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=finite%20memory%20filter" title=" finite memory filter"> finite memory filter</a>, <a href="https://publications.waset.org/abstracts/search?q=infinite%20memory%20filter" title=" infinite memory filter"> infinite memory filter</a>, <a href="https://publications.waset.org/abstracts/search?q=Kalman%20filter" title=" Kalman filter"> Kalman filter</a> </p> <a href="https://publications.waset.org/abstracts/9519/a-packet-loss-probability-estimation-filter-using-most-recent-finite-traffic-measurements" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/9519.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">672</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1793</span> Design Dual Band Band-Pass Filter by Using Stepped Impedance</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Fawzia%20Al-Sakeer">Fawzia Al-Sakeer</a>, <a href="https://publications.waset.org/abstracts/search?q=Hassan%20Aldeeb"> Hassan Aldeeb</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Development in the communications field is proceeding at an amazing speed, which has led researchers to improve and develop electronic circuits by increasing their efficiency and reducing their size to reduce the weight of electronic devices. One of the most important of these circuits is the band-pass filter, which is what made us carry out this research, which aims to use an alternate technology to design a dual band-pass filter by using a stepped impedance microstrip transmission line. We designed a filter that works at two center frequency bands by designing with the ADS program, and the results were excellent, as we obtained the two design frequencies, which are 1 and 3GHz, and the values of insertion loss S11, which was more than 21dB with a small area. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=band%20pass%20filter" title="band pass filter">band pass filter</a>, <a href="https://publications.waset.org/abstracts/search?q=dual%20band%20band-pass%20filter" title=" dual band band-pass filter"> dual band band-pass filter</a>, <a href="https://publications.waset.org/abstracts/search?q=ADS" title=" ADS"> ADS</a>, <a href="https://publications.waset.org/abstracts/search?q=microstrip%20filter" title=" microstrip filter"> microstrip filter</a>, <a href="https://publications.waset.org/abstracts/search?q=stepped%20impedance" title=" stepped impedance"> stepped impedance</a> </p> <a href="https://publications.waset.org/abstracts/177757/design-dual-band-band-pass-filter-by-using-stepped-impedance" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/177757.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">68</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1792</span> Adaptive Motion Compensated Spatial Temporal Filter of Colonoscopy Video </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nidhal%20Azawi">Nidhal Azawi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Colonoscopy procedure is widely used in the world to detect an abnormality. Early diagnosis can help to heal many patients. Because of the unavoidable artifacts that exist in colon images, doctors cannot detect a colon surface precisely. The purpose of this work is to improve the visual quality of colonoscopy videos to provide better information for physicians by removing some artifacts. This work complements a series of work consisting of three previously published papers. In this paper, Optic flow is used for motion compensation, and then consecutive images are aligned/registered to integrate some information to create a new image that has or reveals more information than the original one. Colon images have been classified into informative and noninformative images by using a deep neural network. Then, two different strategies were used to treat informative and noninformative images. Informative images were treated by using Lucas Kanade (LK) with an adaptive temporal mean/median filter, whereas noninformative images are treated by using Lucas Kanade with a derivative of Gaussian (LKDOG) with adaptive temporal median images. A comparison result showed that this work achieved better results than that results in the state- of- the- art strategies for the same degraded colon images data set, which consists of 1000 images. The new proposed algorithm reduced the error alignment by about a factor of 0.3 with a 100% successfully image alignment ratio. In conclusion, this algorithm achieved better results than the state-of-the-art approaches in case of enhancing the informative images as shown in the results section; also, it succeeded to convert the non-informative images that have very few details/no details because of the blurriness/out of focus or because of the specular highlight dominate significant amount of an image to informative images. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=optic%20flow" title="optic flow">optic flow</a>, <a href="https://publications.waset.org/abstracts/search?q=colonoscopy" title=" colonoscopy"> colonoscopy</a>, <a href="https://publications.waset.org/abstracts/search?q=artifacts" title=" artifacts"> artifacts</a>, <a href="https://publications.waset.org/abstracts/search?q=spatial%20temporal%20filter" title=" spatial temporal filter"> spatial temporal filter</a> </p> <a href="https://publications.waset.org/abstracts/131333/adaptive-motion-compensated-spatial-temporal-filter-of-colonoscopy-video" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/131333.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">113</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1791</span> The Effect of Compensating Filter on Image Quality in Lateral Projection of Thoracolumbar Radiography</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Noor%20Arda%20Adrina%20Daud">Noor Arda Adrina Daud</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohd%20Hanafi%20Ali"> Mohd Hanafi Ali</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The compensating filter is placed between the patient and X-ray tube to compensate various density and thickness of human body. The main purpose of this project is to study the effect of compensating filter on image quality in lateral projection of thoracolumbar radiography. The study was performed by an X-ray unit where different thicknesses of aluminum were used as compensating filter. Specifically the relationship between thickness of aluminum, density and noise were evaluated. Results show different thickness of aluminum compensating filter improved the image quality of lateral projection thoracolumbar radiography. The compensating filter of 8.2 mm was considered as the optimal filter to compensate the thoracolumbar junction (T12-L1), 1 mm to compensate lumbar region and 5.9 mm to compensate thorax region. The aluminum wedge compensating filter was designed resulting in an acceptable image quality. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=compensating%20filter" title="compensating filter">compensating filter</a>, <a href="https://publications.waset.org/abstracts/search?q=aluminum" title=" aluminum"> aluminum</a>, <a href="https://publications.waset.org/abstracts/search?q=image%20quality" title=" image quality"> image quality</a>, <a href="https://publications.waset.org/abstracts/search?q=lateral" title=" lateral"> lateral</a>, <a href="https://publications.waset.org/abstracts/search?q=thoracolumbar" title=" thoracolumbar "> thoracolumbar </a> </p> <a href="https://publications.waset.org/abstracts/6135/the-effect-of-compensating-filter-on-image-quality-in-lateral-projection-of-thoracolumbar-radiography" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/6135.pdf" target="_blank" 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