Relating Independent Components to Free-Vibration Modal Responses by S.I. McNeill, D.C. Zimmerman

“…In recent literature, attempts have been made to apply Independent Component Analysis (ICA) techniques to the modal identification problem. …”
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A Method Combining Fractal Analysis and Single Channel ICA for Vibration Noise Reduction by Quanbo Lu, Mei Li

“…Aiming at the problem that real engineering vibration signals are interfered by strong noise, this paper proposes a method combining single channel-independent component analysis (SCICA) and fractal analysis (FD) to reduce the effect of noise on the time-frequency analysis of vibration signals. …”
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Measuring Biometric Sample Quality in terms of Biometric Feature Information in Iris Images by R. Youmaran, A. Adler

“…An example of this method is shown for iris templates processed using Principal-Component Analysis- (PCA-) and Independent-Component Analysis- (ICA-) based feature decomposition schemes. …”
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Transformasi Lontar Babad Lombok Menuju Digitalisasi Berbasis Natural Gradient Flexible (NGF) by Muhammad Tajuddin Anwar, Syahroni Hidayat, Ahmat Adil

“…Salah satu metode yang terbukti mampu untuk memisahkan teks dari latar belakang yang sangat berkorelasi adalah Natural Gradient Flexibel (NGF) berbasiskan Independent Component Analysis (ICA), NGF-ICA. Penelitian ini bertujuan untuk melakukan peningkatan kualitas citra digitalisasi sebelum diumpankan pada database dan sistem informasi yang telah dibangun. …”
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Comparative Analysis of Denoising Techniques for Optimizing EEG Signal Processing by I Putu Agus Eka Darma Udayana, Made Sudarma, I Ketut Gede Darma Putra, I Made Sukarsa, Minho Jo

“…This research aims to improve the quality of EEG signals related to concentration by comparing the effectiveness of two denoising methods, namely Independent Component Analysis (ICA) and Principal Component Analysis (PCA). …”
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Extraction of Fetal Electrocardiogram by Combining Deep Learning and SVD-ICA-NMF Methods by Said Ziani, Yousef Farhaoui, Mohammed Moutaib

“…It is based on the Convolutional Neural Network (CNN) combined with advanced mathematical methods, such as Independent Component Analysis (ICA), Singular Value Decomposition (SVD), and a dimension-reduction technique like Nonnegative Matrix Factorization (NMF). …”
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Support Vector Machine for Behavior-Based Driver Identification System by Huihuan Qian, Yongsheng Ou, Xinyu Wu, Xiaoning Meng, Yangsheng Xu

“…Then we compare fast Fourier transform (FFT), principal component analysis (PCA), and independent component analysis (ICA) for data preprocessing. Using machine learning method of support vector machine (SVM), we derive the individual driving behavior model and we then demonstrate the procedure for recognizing different drivers by analyzing the corresponding models. …”
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Noise Source Separation of an Internal Combustion Engine Based on a Single-Channel Algorithm by Jiachi Yao, Yang Xiang, Sichong Qian, Shuai Wang

“…A single-channel algorithm which combines time-varying filtering-based empirical mode decomposition (TVF-EMD) and robust independent component analysis (RobustICA) methods is proposed to separate them. …”
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Feature Extraction of EEG Signal upon BCI Systems Based on Steady-State Visual Evoked Potentials Using the Ant Colony Optimization Algorithm by S. M. Fernandez-Fraga, M. A. Aceves-Fernandez, J. C. Pedraza-Ortega, S. Tovar-Arriaga

“…As a reference model, we used the Independent Component Analysis method, which has been used in recent research for the removal of nonrelevant and detection of relevant data from the brain’s electrical signals and also allows the collection of information in response to a stimulus and separates the signals that were generated independently in certain zones of the brain.…”
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The Hybrid KICA-GDA-LSSVM Method Research on Rolling Bearing Fault Feature Extraction and Classification by Jiyong Li, Shunming Li, Xiaohong Chen, Lili Wang

“…As feature extraction and classification based on vibration signals are important in condition monitoring technique, and superfluous features may degrade the classification performance, it is needed to extract independent features, so LSSVM (least square support vector machine) based on hybrid KICA-GDA (kernel independent component analysis-generalized discriminate analysis) is presented in this study. …”
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White Matter Hyperintensity Load Modulates Brain Morphometry and Brain Connectivity in Healthy Adults: A Neuroplastic Mechanism? by Matteo De Marco, Riccardo Manca, Micaela Mitolo, Annalena Venneri

“…Voxel-based morphometry was carried out to model grey matter. An independent component analysis was run to extract the anterior and posterior default-mode network, the salience network, the left and right frontoparietal networks, and the visual network. …”
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Volatility Similarity and Spillover Effects in G20 Stock Market Comovements: An ICA-Based ARMA-APARCH-M Approach by Shanglei Chai, Zhen Zhang, Mo Du, Lei Jiang

“…We provide a new approach using an ICA- (independent component analysis-) based ARMA-APARCH-M model to shed light on whether there are spillover effects among G20 stock markets with similar dynamics. …”
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Practically Efficient Blind Speech Separation Using Frequency Band Selection Based on Magnitude Squared Coherence and a Small Dodecahedral Microphone Array by Kazunobu Kondo, Yusuke Mizuno, Takanori Nishino, Kazuya Takeda

“…Blind source separation methods based on frequency domain independent component analysis have shown significant separation performance, and the microphone arrays are small enough to make them portable. …”
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Different Modes of Pitch Perception and Learning-Induced Neuronal Plasticity of the Human Auditory Cortex by Michael Schulte, Arne Knief, Annemarie Seither-Preisler, Christo Pantev

“…Cortical sources of the evoked gamma-band activity were significantly stronger and located more medially after a switch in perception. Independent Component Analysis revealed enhanced synchronization in the gamma-band frequency range. …”
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Investigating surface loading effect on seasonal crustal deformation observed by GNSS in Hong Kong by Hongli Lv, Xiaoxing He, Shunqiang Hu

“…Furthermore, the independent component analysis (ICA) method was performed to extract periodic signals from the GNSS time series. …”
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An environment for complex behaviour detection in bio-potential experiments by Maide Bucolo, Federica Di Grazia, Luigi Fortuna, Mattia Frasca, Francesca Sapuppo

“…It includes sev-eral modules as data importing and loading, data visualization (1D, 2D, 3D),pre-processing (frequency and saturation filtering, statistical analysis), spatio-temporal processing such as power spectrum, independent component analysis(ICA) in spatial and time domain, and nonlinear analysis for the extractionof the maximum Lyapunov exponent and d ∞(d-inifnite) using optimized al-gorithms. …”
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Aberrant Resting-State Functional Connectivity of the Dorsal Attention Network in Tinnitus by Haimeng Hu, Yining Lyu, Shihong Li, Zheng Yuan, Chuntao Ye, Zhao Han, Guangwu Lin

“…Thirty-one patients with persistent tinnitus and thirty-three healthy controls were enrolled in this study. A group independent component analysis (ICA), degree centrality (DC) analysis, and seed-based FC analysis were conducted. …”
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A method of EEG signal feature extraction based on hybrid DWT and EMD by Xiaozhong Geng, Linen Wang, Ping Yu, Weixin Hu, Qipeng Liang, Xintong Zhang, Cheng Chen, Xi Zhang

“…Aiming at the problems of incomplete removal of artifacts and inadequate retention of active components in EEG signal, a fusion method of wavelet transform (WT) and Fast Independent Component Analysis (FastICA) is utilized to preprocess the raw EEG signals. …”
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Integrating fMRI spatial network dynamics and EEG spectral power: insights into resting state connectivity by Souvik Phadikar, Krishna Pusuluri, Armin Iraji, Vince D. Calhoun

“…We estimated time-resolved brain networks using sliding window-based spatially constrained independent component analysis (scICA), producing resting brain networks that evolved over time at the voxel level. …”
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Data-Driven Methodology for the Prediction of Fluid Flow in Ultrasonic Production Logging Data Processing by Hongwei Song, Ming Li, Chaoquan Wu, Qingchuan Wang, Shunke Wei, Mingxing Wang, Wenhui Ma

“…In the same way, the transducer signal is also preprocessed by partial correlation analysis (PCA), and independent features were extracted using independent component analysis (ICA). The extracted features were used as inputs to multilayer back-propagation neural networks, which water cuts as output. …”
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