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11 articles for “Independent Component Analysis (ICA)”
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Research ArticleOpen accessIn the keywordsA Qualitative Analysis of Independent Component Analysis Based Algorithms for the Removal of Artifacts from Electroencephalography SignalsBalaiah Paulchamy, Ilavennila, Jayabalan JayaProblem statement: Independent Component Analysis (ICA) based algorithms applied in the context to remove the artifacts from the EEG signals are evaluated with appropriate metrics and it compares and contrasts the performance of the different methods for such applications. The primary goal is to gain some insight into relative performance of the various methods. Approach: CA is a statistical and … …Journal of Computer Science, Vol. 8, Issue 3 · 6 Jan 2012 · 6,983 accessesView PDFCite
Research ArticleOpen accessIn the keywordsNonnegative Matrix Factorization Features Extraction and Ensemble Methods Classifier for ECG Image ClassificationHussain K. Ibrahim, Shawkat K. Guirguis, Hend A. ElsayedThis study is a novel proposed classification system for ECG image classification. This proposed system uses nonnegative matrix factorization for feature extraction and ensemble methods for classification, and the results are compared with the features extracted by the principal component analysis, kernel principal component analysis, and independent component analysis. Although algorithms find image classification challenging, humans typically find it easy. … …Journal of Computer Science, Vol. 21, Issue 4 · 15 Mar 2025 · 4,863 accessesView PDFCite
Research ArticleOpen accessIn the keywordsBlind Source Separation under Semi-White Gaussian Noise and Uniform Noise: Performance Analysis of ICA, Sobi and JadeRMuna H. Fatnan, Zahir M. Hussain, Hind R. MohammedA comparative study is presented to evaluate the performance of three important Blind Source Separation (BSS) techniques under noisy conditions. The ability of FastICA, SOBI and JadeR is tested in separating several kinds of signals under noisy conditions, including human speech and frequency-modulated (quadratic and linear FM) signals. Additionally, different mixing matrices are used to inspect the effect of the … …Journal of Computer Science, Vol. 15, Issue 1 · 31 Dec 2018 · 7,982 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAdvances in Electromyogram Signal Classification to Improve the Quality of Life for the Disabled and Aged PeopleMd. R. Ahsan, Muhammad I. Ibrahimy, Othman O. KhalifaProblem statement: The social demands for the Quality Of Life (QOL) are increasing with the exponentially expanding silver generation. To improve the QOL of the disabled and elderly people, robotic researchers and biomedical engineers have been trying to combine their techniques into the rehabilitation systems. Various biomedical signals (biosignals) acquired from a specialized tissue, organ, or cell system like the … …Journal of Computer Science, Vol. 6, Issue 7 · 31 Jul 2010 · 8,813 accessesView PDFCite
Research ArticleOpen accessIn the keywordsHarmonic Elimination of Inverters using Blind Signal SeparationB. Justus Rabi, R. ArumugamHarmonics cause major problems in power system due to non linear loads. With the rapid growth in the utilization of the rectifier for critical loads, e.g. In computer or medical equipment the need for high quality uninterruptible power is increasing. The non-linear current drawn by the rectifier loads distort the output of UPS system. Mainly because of output filter impedance … …American Journal of Applied Sciences, Vol. 2, Issue 10 · 31 Oct 2005 · 6,899 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing Electric Vehicle Charging Demand Prediction Using a Novel SAE-DNN Neural Network Model for Probabilistic ForecastingNaga Raju Hari Manikyam, A. Thangam, J. Murugachandravel et al.The rapid growth and widespread adoption of Electric Vehicles (EVs) play a crucial role in the progress of intelligent transportation systems, resulting in a significant decrease in environmentally damaging greenhouse gas emissions. The increase in EV usage has made it crucial to develop charging infrastructure to keep up with the growing demand. Precisely predicting EV charging demand is crucial to … …Journal of Computer Science, Vol. 21, Issue 10 · 11 Dec 2025 · 3,536 accessesView PDFCite
Research ArticleOpen accessIn the abstractAI-Based Feature Extraction Approaches for Dual Modalities of Autism Spectrum Disorder NeuroimagesMeenakshi Malviya, Chandra J, Nagendra NHigh-dimensional data, lower detection accuracy, susceptibility to manual errors, and the requirement of clinical experts are some drawbacks of conventional classification models available for Autism Spectrum Disorder (ASD) detection. To address these challenges and explore the affiliated information from advanced imaging modalities such as Magnetic Resonance Imaging (MRI) in structural MRI (sMRI) and resting state-functional MRI (rs-fMRI), the study applied … …Journal of Computer Science, Vol. 20, Issue 11 · 28 Sep 2024 · 5,087 accessesView PDFCite
Research ArticleOpen accessIn the abstractINDEPENDENT COMPONENT ANALYSIS AND DISCRETE WAVELET TRANSFORM FOR ARTIFACT REMOVAL IN BIOMEDICAL SIGNAL PROCESSINGSalvatore Calcagno, Fabio La Foresta, Mario VersaciRecent works have shown that artifact removal in biomedical signals can be performed by using Discrete Wavelet Transform (DWT) or Independent Component Analysis (ICA). It results often very difficult to remove some artifacts because they could be superimposed on the recordings and they could corrupt the signals in the frequency domain. The two conditions could compromise the performance of both … …American Journal of Applied Sciences, Vol. 11, Issue 1 · 27 Nov 2013 · 7,848 accessesView PDFCite
Research ArticleOpen accessIn the abstractIMPROVING INDEPENDENT COMPONENT ANALYSIS USING SUPPORT VECTOR MACHINES FOR MULTIMODAL IMAGE FUSIOND. Egfin Nirmala, A. Bibin Sam Paul, V. VaidehiThe objective of this study is to combine multiple images of a scene acquired by different sensors to create a new image with all important information from the input images. Recent studies show that bases trained using Independent Component Analysis (ICA) is effective in multisensor fusion and has improved performance over traditional wavelet approaches. In the ICA based fusion, the … …Journal of Computer Science, Vol. 9, Issue 9 · 6 Aug 2013 · 7,272 accessesView PDFCite
Research ArticleOpen accessIn the abstractComparative Evaluation of Adaptive Filter and Neuro-Fuzzy Filter in Artifacts Removal From Electroencephalogram SignalPaulchamy Balaiah, IlavennilaProblem statement: This study presents an effective method for removing mixed artifacts (EOG-Electro-ocular gram, ECG-Electrocardiogram, EMG-Electromyogram) from the EEG-Electroencephalogram records. The noise sources increases the difficulty in analyzing the EEG and obtaining clinical information. EEG signals are multidimensional, non-stationary (i.e., statistical properties are not invariant in time), time domain biological signals, which are not reproducible. It is supposed to contain … …American Journal of Applied Sciences, Vol. 9, Issue 10 · 15 Aug 2012 · 7,087 accessesView PDFCite