Reduction of Multidimensional Image Characteristics Based on Improved KICA by Jia Dongyao, Ai Yanke, Zou Shengxiong

“…Dimensionality reduction and optimization of characteristic parameter model based on improved kernel independent component analysis are proposed in this paper; the independent primitives are obtained by KICA (kernel independent component analysis) algorithm to construct an independent group subspace, while using 2DPCA (2D principal component analysis) algorithm to complete the second order related to data and further reduce the dimension in the above method. …”
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Comprehensive Monitoring of Complex Industrial Processes with Multiple Characteristics by Chenxing Xu, Jiarula Yasenjiang, Pengfei Cui, Shengpeng Zhang, Xin Zhang

“…To address this problem, a hybrid fault detection model based on PCA-KPCA-ICA-KICA-BI (Bayesian inference) is proposed, taking into account the advantages of principal component analysis (PCA), kernel principal component analysis (KPCA), independent component analysis (ICA), and kernel independent component analysis (KICA) in terms of dimensionality reduction and feature extraction. …”
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Independent semantic feature extraction algorithm based on short text by HU Jia-ni, GUO Jun, DENG Wei-hong, XU Wei-ran

“…An independent semantic feature extraction algorithm was proposed,aiming at reducing the sparseness of short text and enhancing its capability of semantic expression.The algorithm first makes use of latent semantic indexing to re-duce the dimension and wipe off noise,and then it introduces independent component analysis to extract statistic inde-pendent and semantic features.Experimental results prove the feasibility of the algorithm and demonstrate it is superior to latent semantic indexing.…”
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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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Polarization demultiplexing by ICA in a polarization multiplexing system with both PMD and PDL by Ling ZHAO, Gui-jun HU, Jin-hua LV, Gong-yu LI, Li LI

“…Due to polarization mode dispersion(PMD)and polarizat dependent loss(PDL)in a system,the coherent detection scheme was chosen at the receiver side of the system and T-CMN algorithm was used to separate the polariza-tion multiplexed signals.Simulation results show that after demultiplexed by independent component analysis(ICA),the transmission quality of polarization signals is obviously improved,and when the optical signal to noise ratio of the sys-tem is greater than 20.86 dB,the bit error rate can be kept lower than10^{- 9},which meets the requirement of a communica-tion system.…”
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ROLLING BEARING FAULT DIAGNOSIS BASED ON LMD AND ICA by CHEN ChongYang, XIONG BangShu, HUANG JianPing, MO Yan, LI XinMin

“…For the problem of Local Mean Decomposition（ LMD） was easily affected by noise interference when in the extraction of fault features,a rolling bearing fault diagnosis method which based on LMD and Independent Component Analysis（ ICA） was proposed. Firstly,original signal was decomposed into a series of production functions（ PF） by the LMD method.Secondly,the estimate of PF was obtained after the PF components had been separated by ICA method,and the noise was effectively removed. …”
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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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Blind detection of orthogonal space-time block coding based on ICA schemes by GU Bo1, LIU Ju1, XU Hong-ji1

“…However the decoding required accurate channel state information （CSI）, which strongly determined the system per-formance. The independent component analysis （ICA） based blind source separation （BSS） techniques could be used to detect the transmitted signals without channel estimation. …”
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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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Research on Background Noise Separation of Reducers Based on VMD and FastICA by Li Weilin, Jiang Yangming, Zhang Zhongjie, Liu Ting, Lin Ting, Cheng Xu, Chen Feng, Wang Keyu, Zeng Hao

“…Aiming at the problem that the noise data acquisition environment of the noise test stand is highly disturbed and difficult to be eliminated, a noise signal decomposition based on variational modal decomposition (VMD) and fast independent component analysis (FastICA) and a background noise component identification and noise reduction method based on signal correlation analysis were proposed. …”
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