Multi-Harmonic Source Localization Based on Sparse Component Analysis and Minimum Conditional Entropy [PDF]
Entropy, 2020 Aiming at the fact that the independent component analysis algorithm requires more measurement points and cannot solve the problem of harmonic source location under underdetermined conditions, a new method based on sparse component analysis and minimum ...
Yongzhen Du, Honggeng Yang, Xiaoyang Ma
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Sparse Component Analysis Using Time-Frequency Representations for Operational Modal Analysis [PDF]
Sensors, 2015 Sparse component analysis (SCA) has been widely used for blind source separation(BSS) for many years. Recently, SCA has been applied to operational modal analysis (OMA), which is also known as output-only modal identification.
Shaoqian Qin, Jie Guo, Changan Zhu
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Sparse Component Analysis (SCA) Based on Adaptive Time—Frequency Thresholding for Underdetermined Blind Source Separation (UBSS) [PDF]
Sensors, 2023 Blind source separation (BSS) recovers source signals from observations without knowing the mixing process or source signals. Underdetermined blind source separation (UBSS) occurs when there are fewer mixes than source signals. Sparse component analysis (
Norsalina Hassan, Dzati Athiar Ramli
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Blind Fault Extraction of Rolling-Bearing Compound Fault Based on Improved Morphological Filtering and Sparse Component Analysis [PDF]
Sensors, 2022 In order to effectively separate and extract bearing composite faults, in view of the non-linearity, strong interference and unknown number of fault source signals of the measured fault signals, a composite fault-diagnosis blind extraction method based ...
Wensong Xie, Jun Zhou, Tao Liu
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Diagnosis of Compound Fault Using Sparsity Promoted-Based Sparse Component Analysis [PDF]
Sensors, 2017 Compound faults often occur in rotating machinery, which increases the difficulty of fault diagnosis. In this case, blind source separation, which usually includes independent component analysis (ICA) and sparse component analysis (SCA), was proposed to ...
Yansong Hao +4 more
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Robust sparse principal component analysis. [PDF]
SSRN Electronic Journal, 2011 A method for principal component analysis is proposed that is sparse and robust at the same time. The sparsity delivers principal components that have loadings on a small number of variables, making them easier to interpret.
Croux, Christophe +2 more
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Craniofacial similarity analysis through sparse principal component analysis.
PLoS ONE, 2017 The computer-aided craniofacial reconstruction (CFR) technique has been widely used in the fields of criminal investigation, archaeology, anthropology and cosmetic surgery.
Junli Zhao +7 more
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Bayesian orthogonal component analysis for sparse representation [PDF]
IEEE Transactions on Signal Processing, 2010 This paper addresses the problem of identifying a lower dimensional space where observed data can be sparsely represented. This under-complete dictionary learning task can be formulated as a blind separation problem of sparse sources linearly mixed with ...
Dobigeon, Nicolas, Tourneret, Jean-Yves
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Retraction: Craniofacial similarity analysis through sparse principal component analysis
PLoS ONEPLOS One Editors
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Demixed Sparse Principal Component Analysis Through Hybrid Structural Regularizers
IEEE Access, 2021 Recently, the sparse representation of multivariate data has gained great popularity in real-world applications like neural activity analysis. Many previous analyses for these data utilize sparse principal component analysis (SPCA) to obtain a sparse ...
Yan Zhang, Haoqing Xu
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