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estimation problem</title> <meta name="description" content="Search results for: statistical estimation problem"> <meta name="keywords" content="statistical estimation problem"> <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> 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action="https://publications.waset.org/abstracts/search"> <div 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="statistical estimation problem"> <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> 12354</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: statistical estimation problem</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">12354</span> Characteristic Function in Estimation of Probability Distribution Moments </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Vladimir%20S.%20Timofeev">Vladimir S. Timofeev</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this article the problem of distributional moments estimation is considered. The new approach of moments estimation based on usage of the characteristic function is proposed. By statistical simulation technique, author shows that new approach has some robust properties. For calculation of the derivatives of characteristic function there is used numerical differentiation. Obtained results confirmed that author’s idea has a certain working efficiency and it can be recommended for any statistical applications. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=characteristic%20function" title="characteristic function">characteristic function</a>, <a href="https://publications.waset.org/abstracts/search?q=distributional%20moments" title=" distributional moments"> distributional moments</a>, <a href="https://publications.waset.org/abstracts/search?q=robustness" title=" robustness"> robustness</a>, <a href="https://publications.waset.org/abstracts/search?q=outlier" title=" outlier"> outlier</a>, <a href="https://publications.waset.org/abstracts/search?q=statistical%20estimation%20problem" title=" statistical estimation problem"> statistical estimation problem</a>, <a href="https://publications.waset.org/abstracts/search?q=statistical%20simulation" title=" statistical simulation"> statistical simulation</a> </p> <a href="https://publications.waset.org/abstracts/11779/characteristic-function-in-estimation-of-probability-distribution-moments" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/11779.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">504</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">12353</span> Bayesian Network and Feature Selection for Rank Deficient Inverse Problem</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kyugneun%20Lee">Kyugneun Lee</a>, <a href="https://publications.waset.org/abstracts/search?q=Ikjin%20Lee"> Ikjin Lee</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Parameter estimation with inverse problem often suffers from unfavorable conditions in the real world. Useless data and many input parameters make the problem complicated or insoluble. Data refinement and reformulation of the problem can solve that kind of difficulties. In this research, a method to solve the rank deficient inverse problem is suggested. A multi-physics system which has rank deficiency caused by response correlation is treated. Impeditive information is removed and the problem is reformulated to sequential estimations using Bayesian network (BN) and subset groups. At first, subset grouping of the responses is performed. Feature selection with singular value decomposition (SVD) is used for the grouping. Next, BN inference is used for sequential conditional estimation according to the group hierarchy. Directed acyclic graph (DAG) structure is organized to maximize the estimation ability. Variance ratio of response to noise is used to pairing the estimable parameters by each response. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Bayesian%20network" title="Bayesian network">Bayesian network</a>, <a href="https://publications.waset.org/abstracts/search?q=feature%20selection" title=" feature selection"> feature selection</a>, <a href="https://publications.waset.org/abstracts/search?q=rank%20deficiency" title=" rank deficiency"> rank deficiency</a>, <a href="https://publications.waset.org/abstracts/search?q=statistical%20inverse%20analysis" title=" statistical inverse analysis"> statistical inverse analysis</a> </p> <a href="https://publications.waset.org/abstracts/75870/bayesian-network-and-feature-selection-for-rank-deficient-inverse-problem" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/75870.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">314</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">12352</span> Depth Estimation in DNN Using Stereo Thermal Image Pairs</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ahmet%20Faruk%20Akyuz">Ahmet Faruk Akyuz</a>, <a href="https://publications.waset.org/abstracts/search?q=Hasan%20Sakir%20Bilge">Hasan Sakir Bilge</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Depth estimation using stereo images is a challenging problem in computer vision. Many different studies have been carried out to solve this problem. With advancing machine learning, tackling this problem is often done with neural network-based solutions. The images used in these studies are mostly in the visible spectrum. However, the need to use the Infrared (IR) spectrum for depth estimation has emerged because it gives better results than visible spectra in some conditions. At this point, we recommend using thermal-thermal (IR) image pairs for depth estimation. In this study, we used two well-known networks (PSMNet, FADNet) with minor modifications to demonstrate the viability of this idea. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=thermal%20stereo%20matching" title="thermal stereo matching">thermal stereo matching</a>, <a href="https://publications.waset.org/abstracts/search?q=deep%20neural%20networks" title="deep neural networks">deep neural networks</a>, <a href="https://publications.waset.org/abstracts/search?q=CNN" title="CNN">CNN</a>, <a href="https://publications.waset.org/abstracts/search?q=Depth%20estimation" title="Depth estimation">Depth estimation</a> </p> <a href="https://publications.waset.org/abstracts/140133/depth-estimation-in-dnn-using-stereo-thermal-image-pairs" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/140133.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">279</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">12351</span> Regression Model Evaluation on Depth Camera Data for Gaze Estimation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=James%20Purnama">James Purnama</a>, <a href="https://publications.waset.org/abstracts/search?q=Riri%20Fitri%20Sari"> Riri Fitri Sari</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We investigate the machine learning algorithm selection problem in the term of a depth image based eye gaze estimation, with respect to its essential difficulty in reducing the number of required training samples and duration time of training. Statistics based prediction accuracy are increasingly used to assess and evaluate prediction or estimation in gaze estimation. This article evaluates Root Mean Squared Error (RMSE) and R-Squared statistical analysis to assess machine learning methods on depth camera data for gaze estimation. There are 4 machines learning methods have been evaluated: Random Forest Regression, Regression Tree, Support Vector Machine (SVM), and Linear Regression. The experiment results show that the Random Forest Regression has the lowest RMSE and the highest R-Squared, which means that it is the best among other methods. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=gaze%20estimation" title="gaze estimation">gaze estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=gaze%20tracking" title=" gaze tracking"> gaze tracking</a>, <a href="https://publications.waset.org/abstracts/search?q=eye%20tracking" title=" eye tracking"> eye tracking</a>, <a href="https://publications.waset.org/abstracts/search?q=kinect" title=" kinect"> kinect</a>, <a href="https://publications.waset.org/abstracts/search?q=regression%20model" title=" regression model"> regression model</a>, <a href="https://publications.waset.org/abstracts/search?q=orange%20python" title=" orange python"> orange python</a> </p> <a href="https://publications.waset.org/abstracts/17938/regression-model-evaluation-on-depth-camera-data-for-gaze-estimation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/17938.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">538</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">12350</span> Monte Carlo Methods and Statistical Inference of Multitype Branching Processes</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ana%20Staneva">Ana Staneva</a>, <a href="https://publications.waset.org/abstracts/search?q=Vessela%20Stoimenova"> Vessela Stoimenova</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A parametric estimation of the MBP with Power Series offspring distribution family is considered in this paper. The MLE for the parameters is obtained in the case when the observable data are incomplete and consist only with the generation sizes of the family tree of MBP. The parameter estimation is calculated by using the Monte Carlo EM algorithm. The estimation for the posterior distribution and for the offspring distribution parameters are calculated by using the Bayesian approach and the Gibbs sampler. The article proposes various examples with bivariate branching processes together with computational results, simulation and an implementation using R. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Bayesian" title="Bayesian">Bayesian</a>, <a href="https://publications.waset.org/abstracts/search?q=branching%20processes" title=" branching processes"> branching processes</a>, <a href="https://publications.waset.org/abstracts/search?q=EM%20algorithm" title=" EM algorithm"> EM algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=Gibbs%20sampler" title=" Gibbs sampler"> Gibbs sampler</a>, <a href="https://publications.waset.org/abstracts/search?q=Monte%20Carlo%20methods" title=" Monte Carlo methods"> Monte Carlo methods</a>, <a href="https://publications.waset.org/abstracts/search?q=statistical%20estimation" title=" statistical estimation"> statistical estimation</a> </p> <a href="https://publications.waset.org/abstracts/63592/monte-carlo-methods-and-statistical-inference-of-multitype-branching-processes" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/63592.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">420</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">12349</span> Introduction of Robust Multivariate Process Capability Indices</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Behrooz%20Khalilloo">Behrooz Khalilloo</a>, <a href="https://publications.waset.org/abstracts/search?q=Hamid%20Shahriari"> Hamid Shahriari</a>, <a href="https://publications.waset.org/abstracts/search?q=Emad%20Roghanian"> Emad Roghanian</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Process capability indices (PCIs) are important concepts of statistical quality control and measure the capability of processes and how much processes are meeting certain specifications. An important issue in statistical quality control is parameter estimation. Under the assumption of multivariate normality, the distribution parameters, mean vector and variance-covariance matrix must be estimated, when they are unknown. Classic estimation methods like method of moment estimation (MME) or maximum likelihood estimation (MLE) makes good estimation of the population parameters when data are not contaminated. But when outliers exist in the data, MME and MLE make weak estimators of the population parameters. So we need some estimators which have good estimation in the presence of outliers. In this work robust M-estimators for estimating these parameters are used and based on robust parameter estimators, robust process capability indices are introduced. The performances of these robust estimators in the presence of outliers and their effects on process capability indices are evaluated by real and simulated multivariate data. The results indicate that the proposed robust capability indices perform much better than the existing process capability indices. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=multivariate%20process%20capability%20indices" title="multivariate process capability indices">multivariate process capability indices</a>, <a href="https://publications.waset.org/abstracts/search?q=robust%20M-estimator" title=" robust M-estimator"> robust M-estimator</a>, <a href="https://publications.waset.org/abstracts/search?q=outlier" title=" outlier"> outlier</a>, <a href="https://publications.waset.org/abstracts/search?q=multivariate%20quality%20control" title=" multivariate quality control"> multivariate quality control</a>, <a href="https://publications.waset.org/abstracts/search?q=statistical%20quality%20control" title=" statistical quality control"> statistical quality control</a> </p> <a href="https://publications.waset.org/abstracts/81586/introduction-of-robust-multivariate-process-capability-indices" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/81586.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">283</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">12348</span> GPS Refinement in Cities Using Statistical Approach</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ashwani%20Kumar">Ashwani Kumar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> GPS plays an important role in everyday life for safe and convenient transportation. While pedestrians use hand held devices to know their position in a city, vehicles in intelligent transport systems use relatively sophisticated GPS receivers for estimating their current position. However, in urban areas where the GPS satellites are occluded by tall buildings, trees and reflections of GPS signals from nearby vehicles, GPS position estimation becomes poor. In this work, an exhaustive GPS data is collected at a single point in urban area under different times of day and under dynamic environmental conditions. The data is analyzed and statistical refinement methods are used to obtain optimal position estimate among all the measured positions. The results obtained are compared with publically available datasets and obtained position estimation refinement results are promising. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=global%20positioning%20system" title="global positioning system">global positioning system</a>, <a href="https://publications.waset.org/abstracts/search?q=statistical%20approach" title=" statistical approach"> statistical approach</a>, <a href="https://publications.waset.org/abstracts/search?q=intelligent%20transport%20systems" title=" intelligent transport systems"> intelligent transport systems</a>, <a href="https://publications.waset.org/abstracts/search?q=least%20squares%20estimation" title=" least squares estimation"> least squares estimation</a> </p> <a href="https://publications.waset.org/abstracts/33278/gps-refinement-in-cities-using-statistical-approach" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/33278.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">288</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">12347</span> A Mathematical Model of Power System State Estimation for Power Flow Solution</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=F.%20Benhamida">F. Benhamida</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Graa"> A. Graa</a>, <a href="https://publications.waset.org/abstracts/search?q=L.%20Benameur"> L. Benameur</a>, <a href="https://publications.waset.org/abstracts/search?q=I.%20Ziane"> I. Ziane</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The state estimation of the electrical power system operation state is very important for supervising task. With the nonlinearity of the AC power flow model, the state estimation problem (SEP) is a nonlinear mathematical problem with many local optima. This paper treat the mathematical model for the SEP and the monitoring of the nonlinear systems of great dimensions with an application on power electrical system, the modelling, the analysis and state estimation synthesis in order to supervise the power system behavior. in fact, it is very difficult, to see impossible, (for reasons of accessibility, techniques and/or of cost) to measure the excessive number of the variables of state in a large-sized system. It is thus important to develop software sensors being able to produce a reliable estimate of the variables necessary for the diagnosis and also for the control. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=power%20system" title="power system">power system</a>, <a href="https://publications.waset.org/abstracts/search?q=state%20estimation" title=" state estimation"> state estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=robustness" title=" robustness"> robustness</a>, <a href="https://publications.waset.org/abstracts/search?q=observability" title=" observability"> observability</a> </p> <a href="https://publications.waset.org/abstracts/36293/a-mathematical-model-of-power-system-state-estimation-for-power-flow-solution" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/36293.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">523</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">12346</span> Electrical Load Estimation Using Estimated Fuzzy Linear Parameters</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Bader%20Alkandari">Bader Alkandari</a>, <a href="https://publications.waset.org/abstracts/search?q=Jamal%20Y.%20Madouh"> Jamal Y. Madouh</a>, <a href="https://publications.waset.org/abstracts/search?q=Ahmad%20M.%20Alkandari"> Ahmad M. Alkandari</a>, <a href="https://publications.waset.org/abstracts/search?q=Anwar%20A.%20Alnaqi"> Anwar A. Alnaqi </a> </p> <p class="card-text"><strong>Abstract:</strong></p> A new formulation of fuzzy linear estimation problem is presented. It is formulated as a linear programming problem. The objective is to minimize the spread of the data points, taking into consideration the type of the membership function of the fuzzy parameters to satisfy the constraints on each measurement point and to insure that the original membership is included in the estimated membership. Different models are developed for a fuzzy triangular membership. The proposed models are applied to different examples from the area of fuzzy linear regression and finally to different examples for estimating the electrical load on a busbar. It had been found that the proposed technique is more suited for electrical load estimation, since the nature of the load is characterized by the uncertainty and vagueness. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20regression" title="fuzzy regression">fuzzy regression</a>, <a href="https://publications.waset.org/abstracts/search?q=load%20estimation" title=" load estimation"> load estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20linear%20parameters" title=" fuzzy linear parameters"> fuzzy linear parameters</a>, <a href="https://publications.waset.org/abstracts/search?q=electrical%20load%20estimation" title=" electrical load estimation"> electrical load estimation</a> </p> <a href="https://publications.waset.org/abstracts/18341/electrical-load-estimation-using-estimated-fuzzy-linear-parameters" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/18341.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">540</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">12345</span> Parameters Estimation of Multidimensional Possibility Distributions</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sergey%20Sorokin">Sergey Sorokin</a>, <a href="https://publications.waset.org/abstracts/search?q=Irina%20Sorokina"> Irina Sorokina</a>, <a href="https://publications.waset.org/abstracts/search?q=Alexander%20Yazenin"> Alexander Yazenin</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We present a solution to the Maxmin u/E parameters estimation problem of possibility distributions in m-dimensional case. Our method is based on geometrical approach, where minimal area enclosing ellipsoid is constructed around the sample. Also we demonstrate that one can improve results of well-known algorithms in fuzzy model identification task using Maxmin u/E parameters estimation. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=possibility%20distribution" title="possibility distribution">possibility distribution</a>, <a href="https://publications.waset.org/abstracts/search?q=parameters%20estimation" title=" parameters estimation"> parameters estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=Maxmin%20u%5CE%20estimator" title=" Maxmin u\E estimator"> Maxmin u\E estimator</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20model%20identification" title=" fuzzy model identification"> fuzzy model identification</a> </p> <a href="https://publications.waset.org/abstracts/16751/parameters-estimation-of-multidimensional-possibility-distributions" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/16751.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">470</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">12344</span> Approximation of the Time Series by Fractal Brownian Motion</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Valeria%20Bondarenko">Valeria Bondarenko</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we propose two problems related to fractal Brownian motion. First problem is simultaneous estimation of two parameters, Hurst exponent and the volatility, that describe this random process. Numerical tests for the simulated fBm provided an efficient method. Second problem is approximation of the increments of the observed time series by a power function by increments from the fractional Brownian motion. Approximation and estimation are shown on the example of real data, daily deposit interest rates. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fractional%20Brownian%20motion" title="fractional Brownian motion">fractional Brownian motion</a>, <a href="https://publications.waset.org/abstracts/search?q=Gausssian%20processes" title=" Gausssian processes"> Gausssian processes</a>, <a href="https://publications.waset.org/abstracts/search?q=approximation" title=" approximation"> approximation</a>, <a href="https://publications.waset.org/abstracts/search?q=time%20series" title=" time series"> time series</a>, <a href="https://publications.waset.org/abstracts/search?q=estimation%20of%20properties%20of%20the%20model" title=" estimation of properties of the model"> estimation of properties of the model</a> </p> <a href="https://publications.waset.org/abstracts/4285/approximation-of-the-time-series-by-fractal-brownian-motion" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/4285.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">376</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">12343</span> Comparison of Statistical Methods for Estimating Missing Precipitation Data in the River Subbasin Lenguazaque, Colombia</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Miguel%20Ca%C3%B1on">Miguel Cañon</a>, <a href="https://publications.waset.org/abstracts/search?q=Darwin%20Mena"> Darwin Mena</a>, <a href="https://publications.waset.org/abstracts/search?q=Ivan%20Cabeza"> Ivan Cabeza</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this work was compared and evaluated the applicability of statistical methods for the estimation of missing precipitations data in the basin of the river Lenguazaque located in the departments of Cundinamarca and Boyacá, Colombia. The methods used were the method of simple linear regression, distance rate, local averages, mean rates, correlation with nearly stations and multiple regression method. The analysis used to determine the effectiveness of the methods is performed by using three statistical tools, the correlation coefficient (r2), standard error of estimation and the test of agreement of Bland and Altmant. The analysis was performed using real rainfall values removed randomly in each of the seasons and then estimated using the methodologies mentioned to complete the missing data values. So it was determined that the methods with the highest performance and accuracy in the estimation of data according to conditions that were counted are the method of multiple regressions with three nearby stations and a random application scheme supported in the precipitation behavior of related data sets. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=statistical%20comparison" title="statistical comparison">statistical comparison</a>, <a href="https://publications.waset.org/abstracts/search?q=precipitation%20data" title=" precipitation data"> precipitation data</a>, <a href="https://publications.waset.org/abstracts/search?q=river%20subbasin" title=" river subbasin"> river subbasin</a>, <a href="https://publications.waset.org/abstracts/search?q=Bland%20and%20Altmant" title=" Bland and Altmant "> Bland and Altmant </a> </p> <a href="https://publications.waset.org/abstracts/21617/comparison-of-statistical-methods-for-estimating-missing-precipitation-data-in-the-river-subbasin-lenguazaque-colombia" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/21617.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">467</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">12342</span> Parameter Estimation of False Dynamic EIV Model with Additive Uncertainty</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Dalvinder%20Kaur%20Mangal">Dalvinder Kaur Mangal</a> </p> <p class="card-text"><strong>Abstract:</strong></p> For the past decade, noise corrupted output measurements have been a fundamental research problem to be investigated. On the other hand, the estimation of the parameters for linear dynamic systems when also the input is affected by noise is recognized as more difficult problem which only recently has received increasing attention. Representations where errors or measurement noises/disturbances are present on both the inputs and outputs are usually called errors-in-variables (EIV) models. These disturbances may also have additive effects which are also considered in this paper. Parameter estimation of false EIV problem using equation error, output error and iterative prefiltering identification schemes with and without additive uncertainty, when only the output observation is corrupted by noise has been dealt in this paper. The comparative study of these three schemes has also been carried out. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=errors-in-variable%20%28EIV%29" title="errors-in-variable (EIV)">errors-in-variable (EIV)</a>, <a href="https://publications.waset.org/abstracts/search?q=false%20EIV" title=" false EIV"> false EIV</a>, <a href="https://publications.waset.org/abstracts/search?q=equation%20error" title=" equation error"> equation error</a>, <a href="https://publications.waset.org/abstracts/search?q=output%20error" title=" output error"> output error</a>, <a href="https://publications.waset.org/abstracts/search?q=iterative%20prefiltering" title=" iterative prefiltering"> iterative prefiltering</a>, <a href="https://publications.waset.org/abstracts/search?q=Gaussian%20noise" title=" Gaussian noise"> Gaussian noise</a> </p> <a href="https://publications.waset.org/abstracts/9427/parameter-estimation-of-false-dynamic-eiv-model-with-additive-uncertainty" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/9427.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">491</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">12341</span> Hybrid Subspace Approach for Time Delay Estimation in MIMO Systems</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mojtaba%20Saeedinezhad">Mojtaba Saeedinezhad</a>, <a href="https://publications.waset.org/abstracts/search?q=Sarah%20Yousefi"> Sarah Yousefi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we present a hybrid subspace approach for Time Delay Estimation (TDE) in multivariable systems. While several methods have been proposed for time delay estimation in SISO systems, delay estimation in MIMO systems were always a big challenge. In these systems the existing TDE methods have significant limitations because most of procedures are just based on system response estimation or correlation analysis. We introduce a new hybrid method for TDE in MIMO systems based on subspace identification and explicit output error method; and compare its performance with previously introduced procedures in presence of different noise levels and in a statistical manner. Then the best method is selected with multi objective decision making technique. It is shown that the performance of new approach is much better than the existing methods, even in low signal-to-noise conditions. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=system%20identification" title="system identification">system identification</a>, <a href="https://publications.waset.org/abstracts/search?q=time%20delay%20estimation" title=" time delay estimation"> time delay estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=ARX" title=" ARX"> ARX</a>, <a href="https://publications.waset.org/abstracts/search?q=OE" title=" OE"> OE</a>, <a href="https://publications.waset.org/abstracts/search?q=merit%20ratio" title=" merit ratio"> merit ratio</a>, <a href="https://publications.waset.org/abstracts/search?q=multi%20variable%20decision%20making" title=" multi variable decision making"> multi variable decision making</a> </p> <a href="https://publications.waset.org/abstracts/48722/hybrid-subspace-approach-for-time-delay-estimation-in-mimo-systems" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/48722.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">346</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">12340</span> A Mixing Matrix Estimation Algorithm for Speech Signals under the Under-Determined Blind Source Separation Model</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jing%20Wu">Jing Wu</a>, <a href="https://publications.waset.org/abstracts/search?q=Wei%20Lv"> Wei Lv</a>, <a href="https://publications.waset.org/abstracts/search?q=Yibing%20Li"> Yibing Li</a>, <a href="https://publications.waset.org/abstracts/search?q=Yuanfan%20You"> Yuanfan You</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The separation of speech signals has become a research hotspot in the field of signal processing in recent years. It has many applications and influences in teleconferencing, hearing aids, speech recognition of machines and so on. The sounds received are usually noisy. The issue of identifying the sounds of interest and obtaining clear sounds in such an environment becomes a problem worth exploring, that is, the problem of blind source separation. This paper focuses on the under-determined blind source separation (UBSS). Sparse component analysis is generally used for the problem of under-determined blind source separation. The method is mainly divided into two parts. Firstly, the clustering algorithm is used to estimate the mixing matrix according to the observed signals. Then the signal is separated based on the known mixing matrix. In this paper, the problem of mixing matrix estimation is studied. This paper proposes an improved algorithm to estimate the mixing matrix for speech signals in the UBSS model. The traditional potential algorithm is not accurate for the mixing matrix estimation, especially for low signal-to noise ratio (SNR).In response to this problem, this paper considers the idea of an improved potential function method to estimate the mixing matrix. The algorithm not only avoids the inuence of insufficient prior information in traditional clustering algorithm, but also improves the estimation accuracy of mixing matrix. This paper takes the mixing of four speech signals into two channels as an example. The results of simulations show that the approach in this paper not only improves the accuracy of estimation, but also applies to any mixing matrix. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=DBSCAN" title="DBSCAN">DBSCAN</a>, <a href="https://publications.waset.org/abstracts/search?q=potential%20function" title=" potential function"> potential function</a>, <a href="https://publications.waset.org/abstracts/search?q=speech%20signal" title=" speech signal"> speech signal</a>, <a href="https://publications.waset.org/abstracts/search?q=the%20UBSS%20model" title=" the UBSS model"> the UBSS model</a> </p> <a href="https://publications.waset.org/abstracts/101455/a-mixing-matrix-estimation-algorithm-for-speech-signals-under-the-under-determined-blind-source-separation-model" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/101455.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">135</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">12339</span> Considering the Reliability of Measurements Issue in Distributed Adaptive Estimation Algorithms</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Wael%20M.%20Bazzi">Wael M. Bazzi</a>, <a href="https://publications.waset.org/abstracts/search?q=Amir%20Rastegarnia"> Amir Rastegarnia</a>, <a href="https://publications.waset.org/abstracts/search?q=Azam%20Khalili"> Azam Khalili</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper we consider the issue of reliability of measurements in distributed adaptive estimation problem. To this aim, we assume a sensor network with different observation noise variance among the sensors and propose new estimation method based on incremental distributed least mean-square (IDLMS) algorithm. The proposed method contains two phases: I) Estimation of each sensors observation noise variance, and II) Estimation of the desired parameter using the estimated observation variances. To deal with the reliability of measurements, in the second phase of the proposed algorithm, the step-size parameter is adjusted for each sensor according to its observation noise variance. As our simulation results show, the proposed algorithm considerably improves the performance of the IDLMS algorithm in the same condition. <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=distributed%20estimation" title=" distributed estimation"> distributed estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=sensor%0D%0Anetwork" title=" sensor network"> sensor network</a>, <a href="https://publications.waset.org/abstracts/search?q=IDLMS%20algorithm" title=" IDLMS algorithm"> IDLMS algorithm</a> </p> <a href="https://publications.waset.org/abstracts/27648/considering-the-reliability-of-measurements-issue-in-distributed-adaptive-estimation-algorithms" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/27648.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">634</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">12338</span> Estimation of Fuel Cost Function Characteristics Using Cuckoo Search</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20R.%20Al-Rashidi">M. R. Al-Rashidi</a>, <a href="https://publications.waset.org/abstracts/search?q=K.%20M.%20El-Naggar"> K. M. El-Naggar</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20F.%20Al-Hajri"> M. F. Al-Hajri</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The fuel cost function describes the electric power generation-cost relationship in thermal plants, hence, it sheds light on economical aspects of power industry. Different models have been proposed to describe this relationship with the quadratic function model being the most popular one. Parameters of second order fuel cost function are estimated in this paper using cuckoo search algorithm. It is a new population based meta-heuristic optimization technique that has been used in this study primarily as an accurate estimation tool. Its main features are flexibility, simplicity, and effectiveness when compared to other estimation techniques. The parameter estimation problem is formulated as an optimization one with the goal being minimizing the error associated with the estimated parameters. A case study is considered in this paper to illustrate cuckoo search promising potential as a valuable estimation and optimization technique. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=cuckoo%20search" title="cuckoo search">cuckoo search</a>, <a href="https://publications.waset.org/abstracts/search?q=parameters%20estimation" title=" parameters estimation"> parameters estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=fuel%20cost%20function" title=" fuel cost function"> fuel cost function</a>, <a href="https://publications.waset.org/abstracts/search?q=economic%20dispatch" title=" economic dispatch"> economic dispatch</a> </p> <a href="https://publications.waset.org/abstracts/25377/estimation-of-fuel-cost-function-characteristics-using-cuckoo-search" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/25377.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">581</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">12337</span> Parameter Estimation via Metamodeling </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sergio%20Haram%20Sarmiento">Sergio Haram Sarmiento</a>, <a href="https://publications.waset.org/abstracts/search?q=Arcady%20Ponosov"> Arcady Ponosov</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Based on appropriate multivariate statistical methodology, we suggest a generic framework for efficient parameter estimation for ordinary differential equations and the corresponding nonlinear models. In this framework classical linear regression strategies is refined into a nonlinear regression by a locally linear modelling technique (known as metamodelling). The approach identifies those latent variables of the given model that accumulate most information about it among all approximations of the same dimension. The method is applied to several benchmark problems, in particular, to the so-called ”power-law systems”, being non-linear differential equations typically used in Biochemical System Theory. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=principal%20component%20analysis" title="principal component analysis">principal component analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=generalized%20law%20of%20mass%20action" title=" generalized law of mass action"> generalized law of mass action</a>, <a href="https://publications.waset.org/abstracts/search?q=parameter%20estimation" title=" parameter estimation"> parameter estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=metamodels" title=" metamodels"> metamodels</a> </p> <a href="https://publications.waset.org/abstracts/23814/parameter-estimation-via-metamodeling" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/23814.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">517</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">12336</span> A Bayesian Multivariate Microeconometric Model for Estimation of Price Elasticity of Demand</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jefferson%20Hernandez">Jefferson Hernandez</a>, <a href="https://publications.waset.org/abstracts/search?q=Juan%20Padilla"> Juan Padilla</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Estimation of price elasticity of demand is a valuable tool for the task of price settling. Given its relevance, it is an active field for microeconomic and statistical research. Price elasticity in the industry of oil and gas, in particular for fuels sold in gas stations, has shown to be a challenging topic given the market and state restrictions, and underlying correlations structures between the types of fuels sold by the same gas station. This paper explores the Lotka-Volterra model for the problem for price elasticity estimation in the context of fuels; in addition, it is introduced multivariate random effects with the purpose of dealing with errors, e.g., measurement or missing data errors. In order to model the underlying correlation structures, the Inverse-Wishart, Hierarchical Half-t and LKJ distributions are studied. Here, the Bayesian paradigm through Markov Chain Monte Carlo (MCMC) algorithms for model estimation is considered. Simulation studies covering a wide range of situations were performed in order to evaluate parameter recovery for the proposed models and algorithms. Results revealed that the proposed algorithms recovered quite well all model parameters. Also, a real data set analysis was performed in order to illustrate the proposed approach. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=price%20elasticity" title="price elasticity">price elasticity</a>, <a href="https://publications.waset.org/abstracts/search?q=volume" title=" volume"> volume</a>, <a href="https://publications.waset.org/abstracts/search?q=correlation%20structures" title=" correlation structures"> correlation structures</a>, <a href="https://publications.waset.org/abstracts/search?q=Bayesian%20models" title=" Bayesian models"> Bayesian models</a> </p> <a href="https://publications.waset.org/abstracts/122666/a-bayesian-multivariate-microeconometric-model-for-estimation-of-price-elasticity-of-demand" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/122666.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">165</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">12335</span> Multi-Subpopulation Genetic Algorithm with Estimation of Distribution Algorithm for Textile Batch Dyeing Scheduling Problem</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nhat-To%20Huynh">Nhat-To Huynh</a>, <a href="https://publications.waset.org/abstracts/search?q=Chen-Fu%20Chien"> Chen-Fu Chien</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Textile batch dyeing scheduling problem is complicated which includes batch formation, batch assignment on machines, batch sequencing with sequence-dependent setup time. Most manufacturers schedule their orders manually that are time consuming and inefficient. More power methods are needed to improve the solution. Motivated by the real needs, this study aims to propose approaches in which genetic algorithm is developed with multi-subpopulation and hybridised with estimation of distribution algorithm to solve the constructed problem for minimising the makespan. A heuristic algorithm is designed and embedded into the proposed algorithms to improve the ability to get out of the local optima. In addition, an empirical study is conducted in a textile company in Taiwan to validate the proposed approaches. The results have showed that proposed approaches are more efficient than simulated annealing algorithm. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=estimation%20of%20distribution%20algorithm" title="estimation of distribution algorithm">estimation of distribution algorithm</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=multi-subpopulation" title=" multi-subpopulation"> multi-subpopulation</a>, <a href="https://publications.waset.org/abstracts/search?q=scheduling" title=" scheduling"> scheduling</a>, <a href="https://publications.waset.org/abstracts/search?q=textile%20dyeing" title=" textile dyeing"> textile dyeing</a> </p> <a href="https://publications.waset.org/abstracts/66139/multi-subpopulation-genetic-algorithm-with-estimation-of-distribution-algorithm-for-textile-batch-dyeing-scheduling-problem" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/66139.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">299</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">12334</span> Single Carrier Frequency Domain Equalization Design to Cope with Narrow Band Jammer</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=So-Young%20Ju">So-Young Ju</a>, <a href="https://publications.waset.org/abstracts/search?q=Sung-Mi%20Jo"> Sung-Mi Jo</a>, <a href="https://publications.waset.org/abstracts/search?q=Eui-Rim%20Jeong"> Eui-Rim Jeong</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, based on the conventional single carrier frequency domain equalization (SC-FDE) structure, we propose a new SC-FDE structure to cope with narrowband jammer. In the conventional SC-FDE structure, channel estimation is performed in the time domain. When a narrowband jammer exists, time-domain channel estimation is very difficult due to high power jamming interference, which degrades receiver performance. To relieve from this problem, a new SC-FDE frame is proposed to enable channel estimation under narrow band jamming environments. In this paper, we proposed a modified SC-FDE structure that can perform channel estimation in the frequency domain and verified the performance via computer simulation. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=channel%20estimation" title="channel estimation">channel estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=jammer" title=" jammer"> jammer</a>, <a href="https://publications.waset.org/abstracts/search?q=pilot" title=" pilot"> pilot</a>, <a href="https://publications.waset.org/abstracts/search?q=SC-FDE" title=" SC-FDE"> SC-FDE</a> </p> <a href="https://publications.waset.org/abstracts/80488/single-carrier-frequency-domain-equalization-design-to-cope-with-narrow-band-jammer" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/80488.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">475</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">12333</span> Least Squares Solution for Linear Quadratic Gaussian Problem with Stochastic Approximation Approach</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sie%20Long%20Kek">Sie Long Kek</a>, <a href="https://publications.waset.org/abstracts/search?q=Wah%20June%20Leong"> Wah June Leong</a>, <a href="https://publications.waset.org/abstracts/search?q=Kok%20Lay%20Teo"> Kok Lay Teo</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Linear quadratic Gaussian model is a standard mathematical model for the stochastic optimal control problem. The combination of the linear quadratic estimation and the linear quadratic regulator allows the state estimation and the optimal control policy to be designed separately. This is known as the separation principle. In this paper, an efficient computational method is proposed to solve the linear quadratic Gaussian problem. In our approach, the Hamiltonian function is defined, and the necessary conditions are derived. In addition to this, the output error is defined and the least-square optimization problem is introduced. By determining the first-order necessary condition, the gradient of the sum squares of output error is established. On this point of view, the stochastic approximation approach is employed such that the optimal control policy is updated. Within a given tolerance, the iteration procedure would be stopped and the optimal solution of the linear-quadratic Gaussian problem is obtained. For illustration, an example of the linear-quadratic Gaussian problem is studied. The result shows the efficiency of the approach proposed. In conclusion, the applicability of the approach proposed for solving the linear quadratic Gaussian problem is highly demonstrated. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=iteration%20procedure" title="iteration procedure">iteration procedure</a>, <a href="https://publications.waset.org/abstracts/search?q=least%20squares%20solution" title=" least squares solution"> least squares solution</a>, <a href="https://publications.waset.org/abstracts/search?q=linear%20quadratic%20Gaussian" title=" linear quadratic Gaussian"> linear quadratic Gaussian</a>, <a href="https://publications.waset.org/abstracts/search?q=output%20error" title=" output error"> output error</a>, <a href="https://publications.waset.org/abstracts/search?q=stochastic%20approximation" title=" stochastic approximation"> stochastic approximation</a> </p> <a href="https://publications.waset.org/abstracts/113018/least-squares-solution-for-linear-quadratic-gaussian-problem-with-stochastic-approximation-approach" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/113018.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">186</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">12332</span> Bayesian Estimation under Different Loss Functions Using Gamma Prior for the Case of Exponential Distribution</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Md.%20Rashidul%20Hasan">Md. Rashidul Hasan</a>, <a href="https://publications.waset.org/abstracts/search?q=Atikur%20Rahman%20Baizid"> Atikur Rahman Baizid</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The Bayesian estimation approach is a non-classical estimation technique in statistical inference and is very useful in real world situation. The aim of this paper is to study the Bayes estimators of the parameter of exponential distribution under different loss functions and then compared among them as well as with the classical estimator named maximum likelihood estimator (MLE). In our real life, we always try to minimize the loss and we also want to gather some prior information (distribution) about the problem to solve it accurately. Here the gamma prior is used as the prior distribution of exponential distribution for finding the Bayes estimator. In our study, we also used different symmetric and asymmetric loss functions such as squared error loss function, quadratic loss function, modified linear exponential (MLINEX) loss function and non-linear exponential (NLINEX) loss function. Finally, mean square error (MSE) of the estimators are obtained and then presented graphically. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Bayes%20estimator" title="Bayes estimator">Bayes estimator</a>, <a href="https://publications.waset.org/abstracts/search?q=maximum%20likelihood%20estimator%20%28MLE%29" title=" maximum likelihood estimator (MLE)"> maximum likelihood estimator (MLE)</a>, <a href="https://publications.waset.org/abstracts/search?q=modified%20linear%20exponential%20%28MLINEX%29%20loss%20function" title=" modified linear exponential (MLINEX) loss function"> modified linear exponential (MLINEX) loss function</a>, <a href="https://publications.waset.org/abstracts/search?q=Squared%20Error%20%28SE%29%20loss%20function" title=" Squared Error (SE) loss function"> Squared Error (SE) loss function</a>, <a href="https://publications.waset.org/abstracts/search?q=non-linear%20exponential%20%28NLINEX%29%20loss%20function" title=" non-linear exponential (NLINEX) loss function"> non-linear exponential (NLINEX) loss function</a> </p> <a href="https://publications.waset.org/abstracts/53902/bayesian-estimation-under-different-loss-functions-using-gamma-prior-for-the-case-of-exponential-distribution" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/53902.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">384</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">12331</span> Modelling Hydrological Time Series Using Wakeby Distribution</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ilaria%20Lucrezia%20Amerise">Ilaria Lucrezia Amerise</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The statistical modelling of precipitation data for a given portion of territory is fundamental for the monitoring of climatic conditions and for Hydrogeological Management Plans (HMP). This modelling is rendered particularly complex by the changes taking place in the frequency and intensity of precipitation, presumably to be attributed to the global climate change. This paper applies the Wakeby distribution (with 5 parameters) as a theoretical reference model. The number and the quality of the parameters indicate that this distribution may be the appropriate choice for the interpolations of the hydrological variables and, moreover, the Wakeby is particularly suitable for describing phenomena producing heavy tails. The proposed estimation methods for determining the value of the Wakeby parameters are the same as those used for density functions with heavy tails. The commonly used procedure is the classic method of moments weighed with probabilities (probability weighted moments, PWM) although this has often shown difficulty of convergence, or rather, convergence to a configuration of inappropriate parameters. In this paper, we analyze the problem of the likelihood estimation of a random variable expressed through its quantile function. The method of maximum likelihood, in this case, is more demanding than in the situations of more usual estimation. The reasons for this lie, in the sampling and asymptotic properties of the estimators of maximum likelihood which improve the estimates obtained with indications of their variability and, therefore, their accuracy and reliability. These features are highly appreciated in contexts where poor decisions, attributable to an inefficient or incomplete information base, can cause serious damages. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=generalized%20extreme%20values" title="generalized extreme values">generalized extreme values</a>, <a href="https://publications.waset.org/abstracts/search?q=likelihood%20estimation" title=" likelihood estimation"> likelihood estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=precipitation%20data" title=" precipitation data"> precipitation data</a>, <a href="https://publications.waset.org/abstracts/search?q=Wakeby%20distribution" title=" Wakeby distribution"> Wakeby distribution</a> </p> <a href="https://publications.waset.org/abstracts/105205/modelling-hydrological-time-series-using-wakeby-distribution" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/105205.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">137</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">12330</span> Orthogonal Regression for Nonparametric Estimation of Errors-In-Variables Models</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Anastasiia%20Yu.%20Timofeeva">Anastasiia Yu. Timofeeva</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Two new algorithms for nonparametric estimation of errors-in-variables models are proposed. The first algorithm is based on penalized regression spline. The spline is represented as a piecewise-linear function and for each linear portion orthogonal regression is estimated. This algorithm is iterative. The second algorithm involves locally weighted regression estimation. When the independent variable is measured with error such estimation is a complex nonlinear optimization problem. The simulation results have shown the advantage of the second algorithm under the assumption that true smoothing parameters values are known. Nevertheless the use of some indexes of fit to smoothing parameters selection gives the similar results and has an oversmoothing effect. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=grade%20point%20average" title="grade point average">grade point average</a>, <a href="https://publications.waset.org/abstracts/search?q=orthogonal%20regression" title=" orthogonal regression"> orthogonal regression</a>, <a href="https://publications.waset.org/abstracts/search?q=penalized%20regression%20spline" title=" penalized regression spline"> penalized regression spline</a>, <a href="https://publications.waset.org/abstracts/search?q=locally%20weighted%20regression" title=" locally weighted regression"> locally weighted regression</a> </p> <a href="https://publications.waset.org/abstracts/11927/orthogonal-regression-for-nonparametric-estimation-of-errors-in-variables-models" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/11927.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">416</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">12329</span> Contrasting The Water Consumption Estimation Methods</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Etienne%20Alain%20Feukeu">Etienne Alain Feukeu</a>, <a href="https://publications.waset.org/abstracts/search?q=L.%20W.%20Snyman"> L. W. Snyman</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Water scarcity is becoming a real issue nowadays. Most countries in the world are facing it in their own way based on their own geographical coordinate and condition. Many countries are facing a challenge of a growing water demand as a result of not only an increased population, economic growth, but also as a pressure of the population dynamic and urbanization. In view to mitigate some of this related problem, an accurate method of water estimation and future prediction, forecast is essential to guarantee not only the sufficient quantity, but also a good water distribution and management system. Beside the fact that several works have been undertaken to address this concern, there is still a considerable disparity between different methods and standard used for water prediction and estimation. Hence this work contrast and compare two well-defined and established methods from two countries (USA and South Africa) to demonstrate the inconsistency when different method and standards are used interchangeably. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=water%20scarcity" title="water scarcity">water scarcity</a>, <a href="https://publications.waset.org/abstracts/search?q=water%20estimation" title=" water estimation"> water estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=water%20prediction" title=" water prediction"> water prediction</a>, <a href="https://publications.waset.org/abstracts/search?q=water%20forecast." title=" water forecast."> water forecast.</a> </p> <a href="https://publications.waset.org/abstracts/142268/contrasting-the-water-consumption-estimation-methods" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/142268.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">201</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">12328</span> Estimating Lost Digital Video Frames Using Unidirectional and Bidirectional Estimation Based on Autoregressive Time Model</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Navid%20Daryasafar">Navid Daryasafar</a>, <a href="https://publications.waset.org/abstracts/search?q=Nima%20Farshidfar"> Nima Farshidfar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this article, we make attempt to hide error in video with an emphasis on the time-wise use of autoregressive (AR) models. To resolve this problem, we assume that all information in one or more video frames is lost. Then, lost frames are estimated using analogous Pixels time information in successive frames. Accordingly, after presenting autoregressive models and how they are applied to estimate lost frames, two general methods are presented for using these models. The first method which is the same standard method of autoregressive models estimates lost frame in unidirectional form. Usually, in such condition, previous frames information is used for estimating lost frame. Yet, in the second method, information from the previous and next frames is used for estimating the lost frame. As a result, this method is known as bidirectional estimation. Then, carrying out a series of tests, performance of each method is assessed in different modes. And, results are compared. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=error%20steganography" title="error steganography">error steganography</a>, <a href="https://publications.waset.org/abstracts/search?q=unidirectional%20estimation" title=" unidirectional estimation"> unidirectional estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=bidirectional%20estimation" title=" bidirectional estimation"> bidirectional estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=AR%20linear%20estimation" title=" AR linear estimation"> AR linear estimation</a> </p> <a href="https://publications.waset.org/abstracts/14175/estimating-lost-digital-video-frames-using-unidirectional-and-bidirectional-estimation-based-on-autoregressive-time-model" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/14175.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">539</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">12327</span> Regret-Regression for Multi-Armed Bandit Problem</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Deyadeen%20Ali%20Alshibani">Deyadeen Ali Alshibani</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In the literature, the multi-armed bandit problem as a statistical decision model of an agent trying to optimize his decisions while improving his information at the same time. There are several different algorithms models and their applications on this problem. In this paper, we evaluate the Regret-regression through comparing with Q-learning method. A simulation on determination of optimal treatment regime is presented in detail. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=optimal" title="optimal">optimal</a>, <a href="https://publications.waset.org/abstracts/search?q=bandit%20problem" title=" bandit problem"> bandit problem</a>, <a href="https://publications.waset.org/abstracts/search?q=optimization" title=" optimization"> optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=dynamic%20programming" title=" dynamic programming"> dynamic programming</a> </p> <a href="https://publications.waset.org/abstracts/18593/regret-regression-for-multi-armed-bandit-problem" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/18593.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">453</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">12326</span> Comparative Study to Evaluate Chronological Age and Dental Age in North Indian Population Using Cameriere Method</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ranjitkumar%20Patil">Ranjitkumar Patil</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Age estimation has its importance in forensic dentistry. Dental age estimation has emerged as an alternative to skeletal age determination. The methods based on stages of tooth formation, as appreciated on radiographs, seems to be more appropriate in the assessment of age than those based on skeletal development. The study was done to evaluate dental age in north Indian population using Cameriere’s method. Aims/Objectives: The study was conducted to assess the dental age of North Indian children using Cameriere’smethodand to compare the chronological age and dental age for validation of the Cameriere’smethod in the north Indian population. A comparative study of 02 year duration on the OPG (using PLANMECA Promax 3D) data of 497 individuals with age ranging from 5 to 15 years was done based on simple random technique ethical approval obtained from the institutional ethical committee. The data was obtained based on inclusion and exclusion criteria was analyzed by a software for dental age estimation. Statistical analysis: Student’s t test was used to compare the morphological variables of males with those of females and to compare observed age with estimated age. Regression formula was also calculated. Results: Present study was a comparative study of 497 subjects with a distribution between male and female, with their dental age assessed by using Panoramic radiograph, following the method described by Cameriere, which is widely accepted. Statistical analysis in our study indicated that gender does not have a significant influence on age estimation. (R2= 0.787). Conclusion: This infers that cameriere’s method can be effectively applied in north Indianpopulation. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Forensic" title="Forensic">Forensic</a>, <a href="https://publications.waset.org/abstracts/search?q=Chronological%20Age" title=" Chronological Age"> Chronological Age</a>, <a href="https://publications.waset.org/abstracts/search?q=Dental%20Age" title=" Dental Age"> Dental Age</a>, <a href="https://publications.waset.org/abstracts/search?q=Skeletal%20Age" title=" Skeletal Age"> Skeletal Age</a> </p> <a href="https://publications.waset.org/abstracts/157891/comparative-study-to-evaluate-chronological-age-and-dental-age-in-north-indian-population-using-cameriere-method" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/157891.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">90</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">12325</span> A Comparative Study to Evaluate Chronological Age and Dental Age in the North Indian Population Using Cameriere's Method</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ranjitkumar%20Patil">Ranjitkumar Patil</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Age estimation has importance in forensic dentistry. Dental age estimation has emerged as an alternative to skeletal age determination. The methods based on stages of tooth formation, as appreciated on radiographs, seem to be more appropriate in the assessment of age than those based on skeletal development. The study was done to evaluate dental age in the north Indian population using Cameriere’s method. Aims/Objectives: The study was conducted to assess the dental age of North Indian children using Cameriere’s method and to compare the chronological age and dental age for validation of the Cameriere’s method in the north Indian population. A comparative study of 02-year duration on the OPG (using PLANMECA Promax 3D) data of 497 individuals with ages ranging from 5 to 15 years was done based on simple random technique ethical approval obtained from institutional ethical committee. The data was obtained based on inclusion and exclusion criteria and was analyzed by software for dental age estimation. Statistical analysis: The student’s t-test was used to compare the morphological variables of males with those of females and to compare observed age with estimated age. The regression formula was also calculated. Results: Present study was a comparative study of 497 subjects with a distribution between males and females, with their dental age assessed by using a Panoramic radiograph, following the method described by Cameriere, which is widely accepted. Statistical analysis in our study indicated that gender does not have a significant influence on age estimation. (R2= 0.787). Conclusion: This infers that Cameriere’s method can be effectively applied to the north Indian population. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=forensic" title="forensic">forensic</a>, <a href="https://publications.waset.org/abstracts/search?q=dental%20age" title=" dental age"> dental age</a>, <a href="https://publications.waset.org/abstracts/search?q=skeletal%20age" title=" skeletal age"> skeletal age</a>, <a href="https://publications.waset.org/abstracts/search?q=chronological%20age" title=" chronological age"> chronological age</a>, <a href="https://publications.waset.org/abstracts/search?q=Cameriere%E2%80%99s%20method" title=" Cameriere’s method"> Cameriere’s method</a> </p> <a href="https://publications.waset.org/abstracts/157885/a-comparative-study-to-evaluate-chronological-age-and-dental-age-in-the-north-indian-population-using-camerieres-method" class="btn btn-primary btn-sm">Procedia</a> <a 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