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signal</title> <meta name="description" content="Search results for: clipped signal"> <meta name="keywords" content="clipped signal"> <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="clipped signal"> <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> 1653</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: clipped signal</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1653</span> Detection of Clipped Fragments in Speech Signals</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sergei%20Aleinik">Sergei Aleinik</a>, <a href="https://publications.waset.org/abstracts/search?q=Yuri%20Matveev"> Yuri Matveev</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper a novel method for the detection of clipping in speech signals is described. It is shown that the new method has better performance than known clipping detection methods, is easy to implement, and is robust to changes in signal amplitude, size of data, etc. Statistical simulation results are presented. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=clipping" title="clipping">clipping</a>, <a href="https://publications.waset.org/abstracts/search?q=clipped%20signal" title=" clipped signal"> clipped signal</a>, <a href="https://publications.waset.org/abstracts/search?q=speech%20signal%20processing" title=" speech signal processing"> speech signal processing</a>, <a href="https://publications.waset.org/abstracts/search?q=digital%20signal%20processing" title=" digital signal processing"> digital signal processing</a> </p> <a href="https://publications.waset.org/abstracts/4816/detection-of-clipped-fragments-in-speech-signals" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/4816.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">392</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">1652</span> Axillary Evaluation with Targeted Axillary Dissection Using Ultrasound-Visible Clips after Neoadjuvant Chemotherapy for Patients with Node-Positive Breast Cancer</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Naomi%20Sakamoto">Naomi Sakamoto</a>, <a href="https://publications.waset.org/abstracts/search?q=Eisuke%20Fukuma"> Eisuke Fukuma</a>, <a href="https://publications.waset.org/abstracts/search?q=Mika%20Nashimoto"> Mika Nashimoto</a>, <a href="https://publications.waset.org/abstracts/search?q=Yoshitomo%20Koshida"> Yoshitomo Koshida</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Background: Selective localization of the metastatic lymph node with clip and removal of clipped nodes with sentinel lymph node (SLN), known as targeted axillary dissection (TAD), reduced false-negative rates (FNR) of SLN biopsy (SLNB) after neoadjuvant chemotherapy (NAC). For the patients who achieved nodal pathologic complete response (pCR), accurate staging of axilla by TAD lead to omit axillary lymph node dissection (ALND), decreasing postoperative arm morbidity without a negative effect on overall survival. This study aimed to investigate the ultrasound (US) identification rate and success removal rate of two kinds of ultrasound-visible clips placed in metastatic lymph nodes during TAD procedure. Methods: This prospective study was conducted using patients with clinically T1-3, N1, 2, M0 breast cancer undergoing NAC followed by surgery. A US-visible clip was placed in the suspicious lymph node under US guidance before neoadjuvant chemotherapy. Before surgery, US examination was performed to evaluate the detection rate of clipped node. During the surgery, the clipped node was removed using several localization techniques, including hook-wire localization, dye-injection, or fluorescence technique, followed by a dual-technique SLNB and resection of palpable nodes if present. For the fluorescence technique, after injection of 0.1-0.2 mL of indocyanine green dye (ICG) into the clipped node, ICG fluorescent imaging was performed using the Photodynamic Eye infrared camera (Hamamatsu Photonics k. k., Shizuoka, Japan). For the dye injection method, 0.1-0.2 mL of pyoktanin blue dye was injected into the clipped node. Results: A total of 29 patients were enrolled. Hydromark™ breast biopsy site markers (Hydromark, T3 shape; Devicor Medical Japan, Tokyo, Japan) was used in 15patients, whereas a UltraCor™ Twirl™ breast marker (Twirl; C.R. Bard, Inc, NJ, USA) was placed in 14 patients. US identified the clipped node marked with the UltraCore Twirl in 100% (14/14) and with the Hydromark in 93.3% (14/15, p = ns). Success removal of clipped node marked with the UltraCore Twirl was achieved in 100% (14/14), whereas the node marked with the Hydromark was removed in 80% (12/15) (p = ns). Conclusions: The ultrasound identification rate differed between the two types of ultrasound-visible clips, which also affected the success removal rate of clipped nodes. Labelling the positive node with a US-highly-visible clip allowed successful TAD. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=breast%20cancer" title="breast cancer">breast cancer</a>, <a href="https://publications.waset.org/abstracts/search?q=neoadjuvant%20chemotherapy" title=" neoadjuvant chemotherapy"> neoadjuvant chemotherapy</a>, <a href="https://publications.waset.org/abstracts/search?q=targeted%20axillary%20dissection" title=" targeted axillary dissection"> targeted axillary dissection</a>, <a href="https://publications.waset.org/abstracts/search?q=breast%20tissue%20marker" title=" breast tissue marker"> breast tissue marker</a>, <a href="https://publications.waset.org/abstracts/search?q=clip" title=" clip"> clip</a> </p> <a href="https://publications.waset.org/abstracts/177380/axillary-evaluation-with-targeted-axillary-dissection-using-ultrasound-visible-clips-after-neoadjuvant-chemotherapy-for-patients-with-node-positive-breast-cancer" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/177380.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">66</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">1651</span> Wavelet Based Residual Method of Detecting GSM Signal Strength Fading</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Danladi%20Ali">Danladi Ali</a>, <a href="https://publications.waset.org/abstracts/search?q=Onah%20Festus%20Iloabuchi"> Onah Festus Iloabuchi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, GSM signal strength was measured in order to detect the type of the signal fading phenomenon using one-dimensional multilevel wavelet residual method and neural network clustering to determine the average GSM signal strength received in the study area. The wavelet residual method predicted that the GSM signal experienced slow fading and attenuated with MSE of 3.875dB. The neural network clustering revealed that mostly -75dB, -85dB and -95dB were received. This means that the signal strength received in the study is a weak signal. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=one-dimensional%20multilevel%20wavelets" title="one-dimensional multilevel wavelets">one-dimensional multilevel wavelets</a>, <a href="https://publications.waset.org/abstracts/search?q=path%20loss" title=" path loss"> path loss</a>, <a href="https://publications.waset.org/abstracts/search?q=GSM%20signal%20strength" title=" GSM signal strength"> GSM signal strength</a>, <a href="https://publications.waset.org/abstracts/search?q=propagation" title=" propagation"> propagation</a>, <a href="https://publications.waset.org/abstracts/search?q=urban%20environment" title=" urban environment"> urban environment</a> </p> <a href="https://publications.waset.org/abstracts/14434/wavelet-based-residual-method-of-detecting-gsm-signal-strength-fading" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/14434.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">338</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">1650</span> Classification of Cochannel Signals Using Cyclostationary Signal Processing and Deep Learning</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Bryan%20Crompton">Bryan Crompton</a>, <a href="https://publications.waset.org/abstracts/search?q=Daniel%20Giger"> Daniel Giger</a>, <a href="https://publications.waset.org/abstracts/search?q=Tanay%20Mehta"> Tanay Mehta</a>, <a href="https://publications.waset.org/abstracts/search?q=Apurva%20Mody"> Apurva Mody</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The task of classifying radio frequency (RF) signals has seen recent success in employing deep neural network models. In this work, we present a combined signal processing and machine learning approach to signal classification for cochannel anomalous signals. The power spectral density and cyclostationary signal processing features of a captured signal are computed and fed into a neural net to produce a classification decision. Our combined signal preprocessing and machine learning approach allows for simpler neural networks with fast training times and small computational resource requirements for inference with longer preprocessing time. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=signal%20processing" title="signal processing">signal processing</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20learning" title=" machine learning"> machine learning</a>, <a href="https://publications.waset.org/abstracts/search?q=cyclostationary%20signal%20processing" title=" cyclostationary signal processing"> cyclostationary signal processing</a>, <a href="https://publications.waset.org/abstracts/search?q=signal%20classification" title=" signal classification"> signal classification</a> </p> <a href="https://publications.waset.org/abstracts/164958/classification-of-cochannel-signals-using-cyclostationary-signal-processing-and-deep-learning" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/164958.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">107</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">1649</span> Voice Signal Processing and Coding in MATLAB Generating a Plasma Signal in a Tesla Coil for a Security System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Juan%20Jimenez">Juan Jimenez</a>, <a href="https://publications.waset.org/abstracts/search?q=Erika%20Yambay"> Erika Yambay</a>, <a href="https://publications.waset.org/abstracts/search?q=Dayana%20Pilco"> Dayana Pilco</a>, <a href="https://publications.waset.org/abstracts/search?q=Brayan%20Parra"> Brayan Parra</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents an investigation of voice signal processing and coding using MATLAB, with the objective of generating a plasma signal on a Tesla coil within a security system. The approach focuses on using advanced voice signal processing techniques to encode and modulate the audio signal, which is then amplified and applied to a Tesla coil. The result is the creation of a striking visual effect of voice-controlled plasma with specific applications in security systems. The article explores the technical aspects of voice signal processing, the generation of the plasma signal, and its relationship to security. The implications and creative potential of this technology are discussed, highlighting its relevance at the forefront of research in signal processing and visual effect generation in the field of security systems. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=voice%20signal%20processing" title="voice signal processing">voice signal processing</a>, <a href="https://publications.waset.org/abstracts/search?q=voice%20signal%20coding" title=" voice signal coding"> voice signal coding</a>, <a href="https://publications.waset.org/abstracts/search?q=MATLAB" title=" MATLAB"> MATLAB</a>, <a href="https://publications.waset.org/abstracts/search?q=plasma%20signal" title=" plasma signal"> plasma signal</a>, <a href="https://publications.waset.org/abstracts/search?q=Tesla%20coil" title=" Tesla coil"> Tesla coil</a>, <a href="https://publications.waset.org/abstracts/search?q=security%20system" title=" security system"> security system</a>, <a href="https://publications.waset.org/abstracts/search?q=visual%20effects" title=" visual effects"> visual effects</a>, <a href="https://publications.waset.org/abstracts/search?q=audiovisual%20interaction" title=" audiovisual interaction"> audiovisual interaction</a> </p> <a href="https://publications.waset.org/abstracts/170828/voice-signal-processing-and-coding-in-matlab-generating-a-plasma-signal-in-a-tesla-coil-for-a-security-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/170828.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">93</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">1648</span> All Optical Wavelength Conversion Based On Four Wave Mixing in Optical Fiber</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Surinder%20Singh">Surinder Singh</a>, <a href="https://publications.waset.org/abstracts/search?q=Gursewak%20Singh%20Lovkesh"> Gursewak Singh Lovkesh</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We have designed wavelength conversion based on four wave mixing in an optical fiber at 10 Gb/s. The power of converted signal increases with increase in signal power. The converted signal power is investigated as a function of input signal power and pump power. On comparison of converted signal power at different value of input signal power, we observe that best converted signal power is obtained at -2 dBm input signal power for both up conversion as well as for down conversion. Further, FWM efficiency, quality factor is observed for increase in input signal power and optical fiber length. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=FWM" title="FWM">FWM</a>, <a href="https://publications.waset.org/abstracts/search?q=optical%20fiiber" title=" optical fiiber"> optical fiiber</a>, <a href="https://publications.waset.org/abstracts/search?q=wavelngth%20converter" title=" wavelngth converter"> wavelngth converter</a>, <a href="https://publications.waset.org/abstracts/search?q=quality" title=" quality"> quality</a> </p> <a href="https://publications.waset.org/abstracts/15950/all-optical-wavelength-conversion-based-on-four-wave-mixing-in-optical-fiber" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/15950.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">1647</span> Transient Signal Generator For Fault Indicator Testing</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mohamed%20Shaban">Mohamed Shaban</a>, <a href="https://publications.waset.org/abstracts/search?q=Ali%20Alfallah"> Ali Alfallah </a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper describes an application for testing of a fault indicator but it could be used for other network protection testing. The application is created in the LabVIEW environment and consists of three parts. The first part of the application is determined for transient phenomenon generation and imitates voltage and current transient signal at ground fault originate. The second part allows to set sequences of trend for each current and voltage output signal, up to six trends for each phase. The last part of the application generates harmonic signal with continuously controllable amplitude of current or voltage output signal and phase shift of each signal can be changed there. Further any sub-harmonics and upper harmonics can be added to selected current output signal <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=signal%20generator-fault%20indicator" title="signal generator-fault indicator">signal generator-fault indicator</a>, <a href="https://publications.waset.org/abstracts/search?q=harmonic%20signal%20generator" title=" harmonic signal generator"> harmonic signal generator</a>, <a href="https://publications.waset.org/abstracts/search?q=voltage%20output" title=" voltage output "> voltage output </a> </p> <a href="https://publications.waset.org/abstracts/19158/transient-signal-generator-for-fault-indicator-testing" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/19158.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">495</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">1646</span> Review: Wavelet New Tool for Path Loss Prediction</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Danladi%20Ali">Danladi Ali</a>, <a href="https://publications.waset.org/abstracts/search?q=Abdullahi%20Mukaila"> Abdullahi Mukaila</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this work, GSM signal strength (power) was monitored in an indoor environment. Samples of the GSM signal strength was measured on mobile equipment (ME). One-dimensional multilevel wavelet is used to predict the fading phenomenon of the GSM signal measured and neural network clustering to determine the average power received in the study area. The wavelet prediction revealed that the GSM signal is attenuated due to the fast fading phenomenon which fades about 7 times faster than the radio wavelength while the neural network clustering determined that -75dBm appeared more frequently followed by -85dBm. The work revealed that significant part of the signal measured is dominated by weak signal and the signal followed more of Rayleigh than Gaussian distribution. This confirmed the wavelet prediction. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=decomposition" title="decomposition">decomposition</a>, <a href="https://publications.waset.org/abstracts/search?q=clustering" title=" clustering"> clustering</a>, <a href="https://publications.waset.org/abstracts/search?q=propagation" title=" propagation"> propagation</a>, <a href="https://publications.waset.org/abstracts/search?q=model" title=" model"> model</a>, <a href="https://publications.waset.org/abstracts/search?q=wavelet" title=" wavelet"> wavelet</a>, <a href="https://publications.waset.org/abstracts/search?q=signal%20strength%20and%20spectral%20efficiency" title=" signal strength and spectral efficiency"> signal strength and spectral efficiency</a> </p> <a href="https://publications.waset.org/abstracts/38599/review-wavelet-new-tool-for-path-loss-prediction" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/38599.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">448</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">1645</span> Carrier Communication through Power Lines</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Pavuluri%20Gopikrishna">Pavuluri Gopikrishna</a>, <a href="https://publications.waset.org/abstracts/search?q=B.%20Neelima"> B. Neelima</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Power line carrier communication means audio power transmission via power line and reception of the amplified audio power at the receiver as in the form of speaker output signal using power line as the channel medium. The main objective of this suggested work is to transmit our message signal after frequency modulation by the help of FM modulator IC LM565 which gives output proportional to the input voltage of the input message signal. And this audio power is received from the power line by the help of isolation circuit and demodulated from IC LM565 which uses the concept of the PLL and produces FM demodulated signal to the listener. Message signal will be transmitted over the carrier signal that will be generated from the FM modulator IC LM565. Using this message signal will not damage because of no direct contact of message signal from the power line, but noise can disturb our information. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=amplification" title="amplification">amplification</a>, <a href="https://publications.waset.org/abstracts/search?q=fm%20demodulator%20ic%20565" title=" fm demodulator ic 565"> fm demodulator ic 565</a>, <a href="https://publications.waset.org/abstracts/search?q=fm%20modulator%20ic%20565" title=" fm modulator ic 565"> fm modulator ic 565</a>, <a href="https://publications.waset.org/abstracts/search?q=phase%20locked%20loop" title=" phase locked loop"> phase locked loop</a>, <a href="https://publications.waset.org/abstracts/search?q=power%20isolation" title=" power isolation"> power isolation</a> </p> <a href="https://publications.waset.org/abstracts/31017/carrier-communication-through-power-lines" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/31017.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">552</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">1644</span> Exploiting Fast Independent Component Analysis Based Algorithm for Equalization of Impaired Baseband Received Signal</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Muhammad%20Umair">Muhammad Umair</a>, <a href="https://publications.waset.org/abstracts/search?q=Syed%20Qasim%20Gilani"> Syed Qasim Gilani</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A technique using Independent Component Analysis (ICA) for blind receiver signal processing is investigated. The problem of the receiver signal processing is viewed as of signal equalization and implementation imperfections compensation. Based on this, a model similar to a general ICA problem is developed for the received signal. Then, the use of ICA technique for blind signal equalization in the time domain is presented. The equalization is regarded as a signal separation problem, since the desired signal is separated from interference terms. This problem is addressed in the paper by over-sampling of the received signal. By using ICA for equalization, besides channel equalization, other transmission imperfections such as Direct current (DC) bias offset, carrier phase and In phase Quadrature phase imbalance will also be corrected. Simulation results for a system using 16-Quadraure Amplitude Modulation(QAM) are presented to show the performance of the proposed scheme. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=blind%20equalization" title="blind equalization">blind equalization</a>, <a href="https://publications.waset.org/abstracts/search?q=blind%20signal%20separation" title=" blind signal separation"> blind signal separation</a>, <a href="https://publications.waset.org/abstracts/search?q=equalization" title=" equalization"> equalization</a>, <a href="https://publications.waset.org/abstracts/search?q=independent%20component%20analysis" title=" independent component analysis"> independent component analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=transmission%20impairments" title=" transmission impairments"> transmission impairments</a>, <a href="https://publications.waset.org/abstracts/search?q=QAM%20receiver" title=" QAM receiver"> QAM receiver</a> </p> <a href="https://publications.waset.org/abstracts/94433/exploiting-fast-independent-component-analysis-based-algorithm-for-equalization-of-impaired-baseband-received-signal" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/94433.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">214</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">1643</span> Minimum Data of a Speech Signal as Special Indicators of Identification in Phonoscopy</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nazaket%20Gazieva">Nazaket Gazieva</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Voice biometric data associated with physiological, psychological and other factors are widely used in forensic phonoscopy. There are various methods for identifying and verifying a person by voice. This article explores the minimum speech signal data as individual parameters of a speech signal. Monozygotic twins are believed to be genetically identical. Using the minimum data of the speech signal, we came to the conclusion that the voice imprint of monozygotic twins is individual. According to the conclusion of the experiment, we can conclude that the minimum indicators of the speech signal are more stable and reliable for phonoscopic examinations. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=phonogram" title="phonogram">phonogram</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=temporal%20characteristics" title=" temporal characteristics"> temporal characteristics</a>, <a href="https://publications.waset.org/abstracts/search?q=fundamental%20frequency" title=" fundamental frequency"> fundamental frequency</a>, <a href="https://publications.waset.org/abstracts/search?q=biometric%20fingerprints" title=" biometric fingerprints"> biometric fingerprints</a> </p> <a href="https://publications.waset.org/abstracts/110332/minimum-data-of-a-speech-signal-as-special-indicators-of-identification-in-phonoscopy" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/110332.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">144</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">1642</span> Study of Three Channel Electrode Position to Detect Optimum Myoelectric Signal on Five Type Grasp Movement</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ilham%20Priadythama">Ilham Priadythama</a>, <a href="https://publications.waset.org/abstracts/search?q=Pringgo%20Widyo%20Laksono"> Pringgo Widyo Laksono</a>, <a href="https://publications.waset.org/abstracts/search?q=Agung%20Pamungkas"> Agung Pamungkas</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Myoelectric is prosthetic, flexible, and offered industrial application has been highly developed and widely used. Myoelectric hand use myoelectric signal from muscle to activate and control the membrane part of hand. Commonly myoelectric signal is detected on human arm from skin surface. So that it only small magnitude signal captured. Detecting myoelectric signal on the skin surface takes proper and consistent procedure. This paper provides preliminary study of electrodes position which gives best signal strength for five basic grasping. Two-position scenario used to place three channel electrodes set. A bi-potential amplifier based on AD620 used to amplify the signal. Finally, the signal was analyzed using DSSF3 software. From this study, we found that grasp type was stronger using first scenario electrode placement while the rest type better with another scenario. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=myoelectric%20signal" title="myoelectric signal">myoelectric signal</a>, <a href="https://publications.waset.org/abstracts/search?q=basic%20grasp" title=" basic grasp"> basic grasp</a>, <a href="https://publications.waset.org/abstracts/search?q=DSSF3" title=" DSSF3"> DSSF3</a>, <a href="https://publications.waset.org/abstracts/search?q=electrode" title=" electrode"> electrode</a>, <a href="https://publications.waset.org/abstracts/search?q=bi-potential%20amplifier" title=" bi-potential amplifier"> bi-potential amplifier</a> </p> <a href="https://publications.waset.org/abstracts/42663/study-of-three-channel-electrode-position-to-detect-optimum-myoelectric-signal-on-five-type-grasp-movement" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/42663.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">324</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">1641</span> Graph Similarity: Algebraic Model and Its Application to Nonuniform Signal Processing</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nileshkumar%20Vishnav">Nileshkumar Vishnav</a>, <a href="https://publications.waset.org/abstracts/search?q=Aditya%20Tatu"> Aditya Tatu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A recent approach of representing graph signals and graph filters as polynomials is useful for graph signal processing. In this approach, the adjacency matrix plays pivotal role; instead of the more common approach involving graph-Laplacian. In this work, we follow the adjacency matrix based approach and corresponding algebraic signal model. We further expand the theory and introduce the concept of similarity of two graphs. The similarity of graphs is useful in that key properties (such as filter-response, algebra related to graph) get transferred from one graph to another. We demonstrate potential applications of the relation between two similar graphs, such as nonuniform filter design, DTMF detection and signal reconstruction. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=graph%20signal%20processing" title="graph signal processing">graph signal processing</a>, <a href="https://publications.waset.org/abstracts/search?q=algebraic%20signal%20processing" title=" algebraic signal processing"> algebraic signal processing</a>, <a href="https://publications.waset.org/abstracts/search?q=graph%20similarity" title=" graph similarity"> graph similarity</a>, <a href="https://publications.waset.org/abstracts/search?q=isospectral%20graphs" title=" isospectral graphs"> isospectral graphs</a>, <a href="https://publications.waset.org/abstracts/search?q=nonuniform%20signal%20processing" title=" nonuniform signal processing"> nonuniform signal processing</a> </p> <a href="https://publications.waset.org/abstracts/59404/graph-similarity-algebraic-model-and-its-application-to-nonuniform-signal-processing" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/59404.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">352</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">1640</span> Vibroacoustic Modulation with Chirp Signal</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Dong%20Liu">Dong Liu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> By sending a high-frequency probe wave and a low-frequency pump wave to a specimen, the vibroacoustic method evaluates the defect’s severity according to the modulation index of the received signal. Many studies experimentally proved the significant sensitivity of the modulation index to the tiny contact type defect. However, it has also been found that the modulation index was highly affected by the frequency of probe or pump waves. Therefore, the chirp signal has been introduced to the VAM method since it can assess multiple frequencies in a relatively short time duration, so the robustness of the VAM method could be enhanced. Consequently, the signal processing method needs to be modified accordingly. Various studies utilized different algorithms or combinations of algorithms for processing the VAM signal method by chirp excitation. These signal process methods were compared and used for processing a VAM signal acquired from the steel samples. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=vibroacoustic%20modulation" title="vibroacoustic modulation">vibroacoustic modulation</a>, <a href="https://publications.waset.org/abstracts/search?q=nonlinear%20acoustic%20modulation" title=" nonlinear acoustic modulation"> nonlinear acoustic modulation</a>, <a href="https://publications.waset.org/abstracts/search?q=nonlinear%20acoustic%20NDT%26E" title=" nonlinear acoustic NDT&E"> nonlinear acoustic NDT&E</a>, <a href="https://publications.waset.org/abstracts/search?q=signal%20processing" title=" signal processing"> signal processing</a>, <a href="https://publications.waset.org/abstracts/search?q=structural%20health%20monitoring" title=" structural health monitoring"> structural health monitoring</a> </p> <a href="https://publications.waset.org/abstracts/155764/vibroacoustic-modulation-with-chirp-signal" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/155764.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">99</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">1639</span> Performance Evaluation of Dynamic Signal Control System for Mixed Traffic Conditions</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Aneesh%20Babu">Aneesh Babu</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20P.%20Anusha"> S. P. Anusha</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A dynamic signal control system combines traditional traffic lights with an array of sensors to intelligently control vehicle and pedestrian traffic. The present study focus on evaluating the performance of dynamic signal control systems for mixed traffic conditions. Data collected from four different approaches to a typical four-legged signalized intersection at Trivandrum city in the Kerala state of India is used for the study. Performance of three other dynamic signal control methods, namely (i) Non-sequential method (ii) Webster design for consecutive signal cycle using flow as input, and (iii) dynamic signal control using RFID delay as input, were evaluated. The evaluation of the dynamic signal control systems was carried out using a calibrated VISSIM microsimulation model. Python programming was used to integrate the dynamic signal control algorithm through the COM interface in VISSIM. The intersection delay obtained from different dynamic signal control methods was compared with the delay obtained from fixed signal control. Based on the study results, it was observed that the intersection delay was reduced significantly by using dynamic signal control methods. The dynamic signal control method using delay from RFID sensors resulted in a higher percentage reduction in delay and hence is a suitable choice for implementation under mixed traffic conditions. The developed dynamic signal control strategies can be implemented in ITS applications under mixed traffic conditions. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=dynamic%20signal%20control" title="dynamic signal control">dynamic signal control</a>, <a href="https://publications.waset.org/abstracts/search?q=intersection%20delay" title=" intersection delay"> intersection delay</a>, <a href="https://publications.waset.org/abstracts/search?q=mixed%20traffic%20conditions" title=" mixed traffic conditions"> mixed traffic conditions</a>, <a href="https://publications.waset.org/abstracts/search?q=RFID%20sensors" title=" RFID sensors"> RFID sensors</a> </p> <a href="https://publications.waset.org/abstracts/156123/performance-evaluation-of-dynamic-signal-control-system-for-mixed-traffic-conditions" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/156123.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">107</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">1638</span> Nonlinear Power Measurement Algorithm of the Input Mix Components of the Noise Signal and Pulse Interference</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Alexey%20V.%20Klyuev">Alexey V. Klyuev</a>, <a href="https://publications.waset.org/abstracts/search?q=Valery%20P.%20Samarin"> Valery P. Samarin</a>, <a href="https://publications.waset.org/abstracts/search?q=Viktor%20F.%20Klyuev"> Viktor F. Klyuev</a>, <a href="https://publications.waset.org/abstracts/search?q=Andrey%20V.%20Klyuev"> Andrey V. Klyuev</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A power measurement algorithm of the input mix components of the noise signal and pulse interference is considered. The algorithm efficiency analysis has been carried out for different interference to signal ratio. Algorithm performance features have been explored by numerical experiment results. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=noise%20signal" title="noise signal">noise signal</a>, <a href="https://publications.waset.org/abstracts/search?q=pulse%20interference" title=" pulse interference"> pulse interference</a>, <a href="https://publications.waset.org/abstracts/search?q=signal%20power" title=" signal power"> signal power</a>, <a href="https://publications.waset.org/abstracts/search?q=spectrum%20width" title=" spectrum width"> spectrum width</a>, <a href="https://publications.waset.org/abstracts/search?q=detection" title=" detection"> detection</a> </p> <a href="https://publications.waset.org/abstracts/1915/nonlinear-power-measurement-algorithm-of-the-input-mix-components-of-the-noise-signal-and-pulse-interference" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/1915.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">337</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">1637</span> Comparative Analysis of Two Approaches to Joint Signal Detection, ToA and AoA Estimation in Multi-Element Antenna Arrays</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Olesya%20Bolkhovskaya">Olesya Bolkhovskaya</a>, <a href="https://publications.waset.org/abstracts/search?q=Alexey%20Davydov"> Alexey Davydov</a>, <a href="https://publications.waset.org/abstracts/search?q=Alexander%20Maltsev"> Alexander Maltsev</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper two approaches to joint signal detection, time of arrival (ToA) and angle of arrival (AoA) estimation in multi-element antenna array are investigated. Two scenarios were considered: first one, when the waveform of the useful signal is known a priori and, second one, when the waveform of the desired signal is unknown. For first scenario, the antenna array signal processing based on multi-element matched filtering (MF) with the following non-coherent detection scheme and maximum likelihood (ML) parameter estimation blocks is exploited. For second scenario, the signal processing based on the antenna array elements covariance matrix estimation with the following eigenvector analysis and ML parameter estimation blocks is applied. The performance characteristics of both signal processing schemes are thoroughly investigated and compared for different useful signals and noise parameters. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=antenna%20array" title="antenna array">antenna array</a>, <a href="https://publications.waset.org/abstracts/search?q=signal%20detection" title=" signal detection"> signal detection</a>, <a href="https://publications.waset.org/abstracts/search?q=ToA" title=" ToA"> ToA</a>, <a href="https://publications.waset.org/abstracts/search?q=AoA%20estimation" title=" AoA estimation"> AoA estimation</a> </p> <a href="https://publications.waset.org/abstracts/11917/comparative-analysis-of-two-approaches-to-joint-signal-detection-toa-and-aoa-estimation-in-multi-element-antenna-arrays" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/11917.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">497</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">1636</span> Musical Tesla Coil Controlled by an Audio Signal Processed in Matlab</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sandra%20Cuenca">Sandra Cuenca</a>, <a href="https://publications.waset.org/abstracts/search?q=Danilo%20Santana"> Danilo Santana</a>, <a href="https://publications.waset.org/abstracts/search?q=Anderson%20Reyes"> Anderson Reyes</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The following project is based on the manipulation of audio signals through the Matlab software, which has an audio signal that is modified, and its resultant obtained through the auxiliary port of the computer is passed through a signal amplifier whose amplified signal is connected to a tesla coil which has a behavior like a vumeter, the flashes at the output of the tesla coil increase and decrease its intensity depending on the audio signal in the computer and also the voltage source from which it is sent. The amplified signal then passes to the tesla coil being shown in the plasma sphere with the respective flashes; this activation is given through the specified parameters that we want to give in the MATLAB algorithm that contains the digital filters for the manipulation of our audio signal sent to the tesla coil to be displayed in a plasma sphere with flashes of the combination of colors commonly pink and purple that varies according to the tone of the song. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=auxiliary%20port" title="auxiliary port">auxiliary port</a>, <a href="https://publications.waset.org/abstracts/search?q=tesla%20coil" title=" tesla coil"> tesla coil</a>, <a href="https://publications.waset.org/abstracts/search?q=vumeter" title=" vumeter"> vumeter</a>, <a href="https://publications.waset.org/abstracts/search?q=plasma%20sphere" title=" plasma sphere"> plasma sphere</a> </p> <a href="https://publications.waset.org/abstracts/170874/musical-tesla-coil-controlled-by-an-audio-signal-processed-in-matlab" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/170874.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">1635</span> Analysis of Interleaving Scheme for Narrowband VoIP System under Pervasive Environment</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Monica%20Sharma">Monica Sharma</a>, <a href="https://publications.waset.org/abstracts/search?q=Harjit%20Pal%20Singh"> Harjit Pal Singh</a>, <a href="https://publications.waset.org/abstracts/search?q=Jasbinder%20Singh"> Jasbinder Singh</a>, <a href="https://publications.waset.org/abstracts/search?q=Manju%20Bala"> Manju Bala</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In Voice over Internet Protocol (VoIP) system, the speech signal is degraded when passed through the network layers. The speech signal is processed through the best effort policy based IP network, which leads to the network degradations including delay, packet loss and jitter. The packet loss is the major issue of the degradation in the VoIP signal quality; even a single lost packet may generate audible distortion in the decoded speech signal. In addition to these network degradations, the quality of the speech signal is also affected by the environmental noises and coder distortions. The signal quality of the VoIP system is improved through the interleaving technique. The performance of the system is evaluated for various types of noises at different network conditions. The performance of the enhanced VoIP signal is evaluated using perceptual evaluation of speech quality (PESQ) measurement for narrow band signal. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=VoIP" title="VoIP">VoIP</a>, <a href="https://publications.waset.org/abstracts/search?q=interleaving" title=" interleaving"> interleaving</a>, <a href="https://publications.waset.org/abstracts/search?q=packet%20loss" title=" packet loss"> packet loss</a>, <a href="https://publications.waset.org/abstracts/search?q=packet%20size" title=" packet size"> packet size</a>, <a href="https://publications.waset.org/abstracts/search?q=background%20noise" title=" background noise "> background noise </a> </p> <a href="https://publications.waset.org/abstracts/14305/analysis-of-interleaving-scheme-for-narrowband-voip-system-under-pervasive-environment" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/14305.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">479</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">1634</span> Development of a Tesla Music Coil from Signal Processing</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Samaniego%20Campoverde%20Jos%C3%A9%20Enrique">Samaniego Campoverde José Enrique</a>, <a href="https://publications.waset.org/abstracts/search?q=Rosero%20Mu%C3%B1oz%20Jorge%20Enrique"> Rosero Muñoz Jorge Enrique</a>, <a href="https://publications.waset.org/abstracts/search?q=Luzcando%20Narea%20Lorena%20Elizabeth"> Luzcando Narea Lorena Elizabeth</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents a practical and theoretical model for the operation of the Tesla coil using digital signal processing. The research is based on the analysis of ten scientific papers exploring the development and operation of the Tesla coil. Starting from the Testa coil, several modifications were carried out on the Tesla coil, with the aim of amplifying the digital signal by making use of digital signal processing. To achieve this, an amplifier with a transistor and digital filters provided by MATLAB software were used, which were chosen according to the characteristics of the signals in question. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=tesla%20coil" title="tesla coil">tesla coil</a>, <a href="https://publications.waset.org/abstracts/search?q=digital%20signal%20process" title=" digital signal process"> digital signal process</a>, <a href="https://publications.waset.org/abstracts/search?q=equalizer" title=" equalizer"> equalizer</a>, <a href="https://publications.waset.org/abstracts/search?q=graphical%20environment" title=" graphical environment"> graphical environment</a> </p> <a href="https://publications.waset.org/abstracts/170965/development-of-a-tesla-music-coil-from-signal-processing" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/170965.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">117</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">1633</span> Forensic Analysis of Signal Messenger on Android</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ward%20Bakker">Ward Bakker</a>, <a href="https://publications.waset.org/abstracts/search?q=Shadi%20Alhakimi"> Shadi Alhakimi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The amount of people moving towards more privacy focused instant messaging applications has grown significantly. Signal is one of these instant messaging applications, which makes Signal interesting for digital investigators. In this research, we evaluate the artifacts that are generated by the Signal messenger for Android. This evaluation was done by using the features that Signal provides to create artifacts, whereafter, we made an image of the internal storage and the process memory. This image was analysed manually. The manual analysis revealed the content that Signal stores in different locations during its operation. From our research, we were able to identify the artifacts and interpret how they were used. We also examined the source code of Signal. Using our obtain knowledge from the source code, we developed a tool that decrypts some of the artifacts using the key stored in the Android Keystore. In general, we found that most artifacts are encrypted and encoded, even after decrypting some of the artifacts. During data visualization, some artifacts were found, such as that Signal does not use relationships between the data. In this research, two interesting groups of artifacts were identified, those related to the database and those stored in the process memory dump. In the database, we found plaintext private- and group chats, and in the memory dump, we were able to retrieve the plaintext access code to the application. Nevertheless, we conclude that Signal contains a wealth of artifacts that could be very valuable to a digital forensic investigation. <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=signal" title=" signal"> signal</a>, <a href="https://publications.waset.org/abstracts/search?q=Android" title=" Android"> Android</a>, <a href="https://publications.waset.org/abstracts/search?q=digital" title=" digital"> digital</a> </p> <a href="https://publications.waset.org/abstracts/145060/forensic-analysis-of-signal-messenger-on-android" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/145060.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">82</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">1632</span> Neural Network Based Path Loss Prediction for Global System for Mobile Communication in an Urban Environment</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Danladi%20Ali">Danladi Ali</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we measured GSM signal strength in the Dnepropetrovsk city in order to predict path loss in study area using nonlinear autoregressive neural network prediction and we also, used neural network clustering to determine average GSM signal strength receive at the study area. The nonlinear auto-regressive neural network predicted that the GSM signal is attenuated with the mean square error (MSE) of 2.6748dB, this attenuation value is used to modify the COST 231 Hata and the Okumura-Hata models. The neural network clustering revealed that -75dB to -95dB is received more frequently. This means that the signal strength received at the study is mostly weak signal <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=one-dimensional%20multilevel%20wavelets" title="one-dimensional multilevel wavelets">one-dimensional multilevel wavelets</a>, <a href="https://publications.waset.org/abstracts/search?q=path%20loss" title=" path loss"> path loss</a>, <a href="https://publications.waset.org/abstracts/search?q=GSM%20signal%20strength" title=" GSM signal strength"> GSM signal strength</a>, <a href="https://publications.waset.org/abstracts/search?q=propagation" title=" propagation"> propagation</a>, <a href="https://publications.waset.org/abstracts/search?q=urban%20environment%20and%20model" title=" urban environment and model"> urban environment and model</a> </p> <a href="https://publications.waset.org/abstracts/14119/neural-network-based-path-loss-prediction-for-global-system-for-mobile-communication-in-an-urban-environment" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/14119.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">382</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">1631</span> Computational Modeling of Load Limits of Carbon Fibre Composite Laminates Subjected to Low-Velocity Impact Utilizing Convolution-Based Fast Fourier Data Filtering Algorithms </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Farhat%20Imtiaz">Farhat Imtiaz</a>, <a href="https://publications.waset.org/abstracts/search?q=Umar%20Farooq"> Umar Farooq</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this work, we developed a computational model to predict ply level failure in impacted composite laminates. Data obtained from physical testing from flat and round nose impacts of 8-, 16-, 24-ply laminates were considered. Routine inspections of the tested laminates were carried out to approximate ply by ply inflicted damage incurred. Plots consisting of load–time, load–deflection, and energy–time history were drawn to approximate the inflicted damages. Impact test generated unwanted data logged due to restrictions on testing and logging systems were also filtered. Conventional filters (built-in, statistical, and numerical) reliably predicted load thresholds for relatively thin laminates such as eight and sixteen ply panels. However, for relatively thick laminates such as twenty-four ply laminates impacted by flat nose impact generated clipped data which can just be de-noised using oscillatory algorithms. The literature search reveals that modern oscillatory data filtering and extrapolation algorithms have scarcely been utilized. This investigation reports applications of filtering and extrapolation of the clipped data utilising fast Fourier Convolution algorithm to predict load thresholds. Some of the results were related to the impact-induced damage areas identified with Ultrasonic C-scans and found to be in acceptable agreement. Based on consistent findings, utilizing of modern data filtering and extrapolation algorithms to data logged by the existing machines has efficiently enhanced data interpretations without resorting to extra resources. The algorithms could be useful for impact-induced damage approximations of similar cases. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fibre%20reinforced%20laminates" title="fibre reinforced laminates">fibre reinforced laminates</a>, <a href="https://publications.waset.org/abstracts/search?q=fast%20Fourier%20algorithms" title=" fast Fourier algorithms"> fast Fourier algorithms</a>, <a href="https://publications.waset.org/abstracts/search?q=mechanical%20testing" title=" mechanical testing"> mechanical testing</a>, <a href="https://publications.waset.org/abstracts/search?q=data%20filtering%20and%20extrapolation" title=" data filtering and extrapolation"> data filtering and extrapolation</a> </p> <a href="https://publications.waset.org/abstracts/94686/computational-modeling-of-load-limits-of-carbon-fibre-composite-laminates-subjected-to-low-velocity-impact-utilizing-convolution-based-fast-fourier-data-filtering-algorithms" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/94686.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">1630</span> Heart Murmurs and Heart Sounds Extraction Using an Algorithm Process Separation</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Fatima%20Mokeddem">Fatima Mokeddem</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The phonocardiogram signal (PCG) is a physiological signal that reflects heart mechanical activity, is a promising tool for curious researchers in this field because it is full of indications and useful information for medical diagnosis. PCG segmentation is a basic step to benefit from this signal. Therefore, this paper presents an algorithm that serves the separation of heart sounds and heart murmurs in case they exist in order to use them in several applications and heart sounds analysis. The separation process presents here is founded on three essential steps filtering, envelope detection, and heart sounds segmentation. The algorithm separates the PCG signal into S1 and S2 and extract cardiac murmurs. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=phonocardiogram%20signal" title="phonocardiogram signal">phonocardiogram signal</a>, <a href="https://publications.waset.org/abstracts/search?q=filtering" title=" filtering"> filtering</a>, <a href="https://publications.waset.org/abstracts/search?q=Envelope" title=" Envelope"> Envelope</a>, <a href="https://publications.waset.org/abstracts/search?q=Detection" title=" Detection"> Detection</a>, <a href="https://publications.waset.org/abstracts/search?q=murmurs" title=" murmurs"> murmurs</a>, <a href="https://publications.waset.org/abstracts/search?q=heart%20sounds" title=" heart sounds"> heart sounds</a> </p> <a href="https://publications.waset.org/abstracts/114970/heart-murmurs-and-heart-sounds-extraction-using-an-algorithm-process-separation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/114970.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">141</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">1629</span> Sparsity Order Selection and Denoising in Compressed Sensing Framework</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mahdi%20Shamsi">Mahdi Shamsi</a>, <a href="https://publications.waset.org/abstracts/search?q=Tohid%20Yousefi%20Rezaii"> Tohid Yousefi Rezaii</a>, <a href="https://publications.waset.org/abstracts/search?q=Siavash%20Eftekharifar"> Siavash Eftekharifar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Compressed sensing (CS) is a new powerful mathematical theory concentrating on sparse signals which is widely used in signal processing. The main idea is to sense sparse signals by far fewer measurements than the Nyquist sampling rate, but the reconstruction process becomes nonlinear and more complicated. Common dilemma in sparse signal recovery in CS is the lack of knowledge about sparsity order of the signal, which can be viewed as model order selection procedure. In this paper, we address the problem of sparsity order estimation in sparse signal recovery. This is of main interest in situations where the signal sparsity is unknown or the signal to be recovered is approximately sparse. It is shown that the proposed method also leads to some kind of signal denoising, where the observations are contaminated with noise. Finally, the performance of the proposed approach is evaluated in different scenarios and compared to an existing method, which shows the effectiveness of the proposed method in terms of order selection as well as denoising. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=compressed%20sensing" title="compressed sensing">compressed sensing</a>, <a href="https://publications.waset.org/abstracts/search?q=data%20denoising" title=" data denoising"> data denoising</a>, <a href="https://publications.waset.org/abstracts/search?q=model%20order%20selection" title=" model order selection"> model order selection</a>, <a href="https://publications.waset.org/abstracts/search?q=sparse%20representation" title=" sparse representation"> sparse representation</a> </p> <a href="https://publications.waset.org/abstracts/31470/sparsity-order-selection-and-denoising-in-compressed-sensing-framework" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/31470.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">483</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">1628</span> Theoretical BER Analyzing of MPSK Signals Based on the Signal Space</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jing%20Qing-feng">Jing Qing-feng</a>, <a href="https://publications.waset.org/abstracts/search?q=Liu%20Danmei"> Liu Danmei</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Based on the optimum detection, signal projection and Maximum A Posteriori (MAP) rule, Proakis has deduced the theoretical BER equation of Gray coded MPSK signals. Proakis analyzed the BER theoretical equations mainly based on the projection of signals, which is difficult to be understood. This article solve the same problem based on the signal space, which explains the vectors relations among the sending signals, received signals and noises. The more explicit and easy-deduced process is illustrated in this article based on the signal space, which can illustrated the relations among the signals and noises clearly. This kind of deduction has a univocal geometry meaning. It can explain the correlation between the production and calculation of BER in vector level. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=MPSK" title="MPSK">MPSK</a>, <a href="https://publications.waset.org/abstracts/search?q=MAP" title=" MAP"> MAP</a>, <a href="https://publications.waset.org/abstracts/search?q=signal%20space" title=" signal space"> signal space</a>, <a href="https://publications.waset.org/abstracts/search?q=BER" title="BER">BER</a> </p> <a href="https://publications.waset.org/abstracts/45896/theoretical-ber-analyzing-of-mpsk-signals-based-on-the-signal-space" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/45896.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">1627</span> Analysis of Matching Pursuit Features of EEG Signal for Mental Tasks Classification </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Zin%20Mar%20Lwin">Zin Mar Lwin</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Brain Computer Interface (BCI) Systems have developed for people who suffer from severe motor disabilities and challenging to communicate with their environment. BCI allows them for communication by a non-muscular way. For communication between human and computer, BCI uses a type of signal called Electroencephalogram (EEG) signal which is recorded from the human„s brain by means of an electrode. The electroencephalogram (EEG) signal is an important information source for knowing brain processes for the non-invasive BCI. Translating human‟s thought, it needs to classify acquired EEG signal accurately. This paper proposed a typical EEG signal classification system which experiments the Dataset from “Purdue University.” Independent Component Analysis (ICA) method via EEGLab Tools for removing artifacts which are caused by eye blinks. For features extraction, the Time and Frequency features of non-stationary EEG signals are extracted by Matching Pursuit (MP) algorithm. The classification of one of five mental tasks is performed by Multi_Class Support Vector Machine (SVM). For SVMs, the comparisons have been carried out for both 1-against-1 and 1-against-all methods. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=BCI" title="BCI">BCI</a>, <a href="https://publications.waset.org/abstracts/search?q=EEG" title=" EEG"> EEG</a>, <a href="https://publications.waset.org/abstracts/search?q=ICA" title=" ICA"> ICA</a>, <a href="https://publications.waset.org/abstracts/search?q=SVM" title=" SVM"> SVM</a> </p> <a href="https://publications.waset.org/abstracts/19307/analysis-of-matching-pursuit-features-of-eeg-signal-for-mental-tasks-classification" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/19307.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">278</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">1626</span> Exact Formulas of the End-To-End Green’s Functions in Non-hermitian Systems</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Haoshu%20Li">Haoshu Li</a>, <a href="https://publications.waset.org/abstracts/search?q=Shaolong%20Wan"> Shaolong Wan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The recent focus has been on directional signal amplification of a signal input at one end of a one-dimensional chain and measured at the other end. The amplification rate is given by the end-to-end Green’s functions of the system. In this work, we derive the exact formulas for the end-to-end Green's functions of non-Hermitian single-band systems. While in the bulk region, it is found that the Green's functions are displaced from the prior established integral formula by O(e⁻ᵇᴸ). The results confirm the correspondence between the signal amplification and the non-Hermitian skin effect. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=non-Hermitian" title="non-Hermitian">non-Hermitian</a>, <a href="https://publications.waset.org/abstracts/search?q=Green%27s%20function" title=" Green's function"> Green's function</a>, <a href="https://publications.waset.org/abstracts/search?q=non-Hermitian%20skin%20effect" title=" non-Hermitian skin effect"> non-Hermitian skin effect</a>, <a href="https://publications.waset.org/abstracts/search?q=signal%20amplification" title=" signal amplification"> signal amplification</a> </p> <a href="https://publications.waset.org/abstracts/149780/exact-formulas-of-the-end-to-end-greens-functions-in-non-hermitian-systems" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/149780.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">141</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">1625</span> Speech Enhancement Using Kalman Filter in Communication</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Eng.%20Alaa%20K.%20Satti%20Salih">Eng. Alaa K. Satti Salih</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Revolutions Applications such as telecommunications, hands-free communications, recording, etc. which need at least one microphone, the signal is usually infected by noise and echo. The important application is the speech enhancement, which is done to remove suppressed noises and echoes taken by a microphone, beside preferred speech. Accordingly, the microphone signal has to be cleaned using digital signal processing DSP tools before it is played out, transmitted, or stored. Engineers have so far tried different approaches to improving the speech by get back the desired speech signal from the noisy observations. Especially Mobile communication, so in this paper will do reconstruction of the speech signal, observed in additive background noise, using the Kalman filter technique to estimate the parameters of the Autoregressive Process (AR) in the state space model and the output speech signal obtained by the MATLAB. The accurate estimation by Kalman filter on speech would enhance and reduce the noise then compare and discuss the results between actual values and estimated values which produce the reconstructed signals. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=autoregressive%20process" title="autoregressive process">autoregressive process</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=Matlab" title=" Matlab"> Matlab</a>, <a href="https://publications.waset.org/abstracts/search?q=noise%20speech" title=" noise speech"> noise speech</a> </p> <a href="https://publications.waset.org/abstracts/7182/speech-enhancement-using-kalman-filter-in-communication" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/7182.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">344</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">1624</span> Subband Coding and Glottal Closure Instant (GCI) Using SEDREAMS Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Harisudha%20Kuresan">Harisudha Kuresan</a>, <a href="https://publications.waset.org/abstracts/search?q=Dhanalakshmi%20Samiappan"> Dhanalakshmi Samiappan</a>, <a href="https://publications.waset.org/abstracts/search?q=T.%20Rama%20Rao"> T. Rama Rao</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In modern telecommunication applications, Glottal Closure Instants location finding is important and is directly evaluated from the speech waveform. Here, we study the GCI using Speech Event Detection using Residual Excitation and the Mean Based Signal (SEDREAMS) algorithm. Speech coding uses parameter estimation using audio signal processing techniques to model the speech signal combined with generic data compression algorithms to represent the resulting modeled in a compact bit stream. This paper proposes a sub-band coder SBC, which is a type of transform coding and its performance for GCI detection using SEDREAMS are evaluated. In SBCs code in the speech signal is divided into two or more frequency bands and each of these sub-band signal is coded individually. The sub-bands after being processed are recombined to form the output signal, whose bandwidth covers the whole frequency spectrum. Then the signal is decomposed into low and high-frequency components and decimation and interpolation in frequency domain are performed. The proposed structure significantly reduces error, and precise locations of Glottal Closure Instants (GCIs) are found using SEDREAMS algorithm. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=SEDREAMS" title="SEDREAMS">SEDREAMS</a>, <a href="https://publications.waset.org/abstracts/search?q=GCI" title=" GCI"> GCI</a>, <a href="https://publications.waset.org/abstracts/search?q=SBC" title=" SBC"> SBC</a>, <a href="https://publications.waset.org/abstracts/search?q=GOI" title=" GOI"> GOI</a> </p> <a href="https://publications.waset.org/abstracts/56336/subband-coding-and-glottal-closure-instant-gci-using-sedreams-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/56336.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">356</span> </span> </div> </div> <ul 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