Comparison of Statistical Underlying Systematic Risk Factors and Betas Driving Returns on Equities
Revista Mexicana de Economía y Finanzas Nueva Época REMEF, 2021 The objective of this paper is to compare four dimension reduction techniques used for extracting the underlying systematic risk factors driving returns on equities of the Mexican Market.
Rogelio Ladrón de Guevara Cortés +2 more
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A Unifying View on Blind Source Separation of Convolutive Mixtures based on Independent Component Analysis [PDF]
, 2022 Andreas Brendel +2 more
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A stochastic algorithm for probabilistic independent component analysis
, 2012 The decomposition of a sample of images on a relevant subspace is a recurrent problem in many different fields from Computer Vision to medical image analysis.
Allassonniére, Stéphanie +1 more
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Advances in Mechanical Engineering, 2017 In this article, for the first time, the optical flow and principal component analysis followed independent component analysis are combined for monitoring the motion process of robotic-arm-based system.
Song Fan +3 more
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Data-driven human transcriptomic modules determined by independent component analysis
BMC Bioinformatics, 2018 Background Analyzing the human transcriptome is crucial in advancing precision medicine, and the plethora of over half a million human microarray samples in the Gene Expression Omnibus (GEO) has enabled us to better characterize biological processes at ...
Weizhuang Zhou, Russ B. Altman
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Robust Independent Component Analysis Based on Two Scatter Matrices
Austrian Journal of Statistics, 2016 Oja, Sirkiä, and Eriksson (2006) and Ollila, Oja, and Koivunen (2007) showed that, under general assumptions, any two scatter matrices with the so called independent components property can be used to estimate the unmixing matrix for the independent ...
Klaus Nordhausen, Hannu Oja, Esa Ollila
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Robust Independent Component Analysis via Minimum Divergence Estimation [PDF]
, 2012 Independent component analysis (ICA) has been shown to be useful in many applications. However, most ICA methods are sensitive to data contamination and outliers. In this article we introduce a general minimum U-divergence framework for ICA, which covers
Chen, Peng-Wen +4 more
core
A Feature-Selective Independent Component Analysis Method for Functional MRI
International Journal of Biomedical Imaging, 2007 In this work, we propose a simple and effective scheme to incorporate prior knowledge about the sources of interest (SOIs) in independent component analysis (ICA) and apply the method to estimate brain activations from functional magnetic resonance ...
Yi-Ou Li, Tülay Adali, Vince D. Calhoun
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Independent component analysis based on quantum particle swarm optimization
Egyptian Informatics Journal, 2018 One of the Digital Signal Processing problems is a Blind Source Separation (BSS). There are some of methods are employed to solve this problem which are so-called Independent Component Analysis (ICA) which based on the statistical distribution of the ...
Nidaa AbdulMohsin Abbas +1 more
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Estimation of the Number of Endmembers in Hyperspectral Images Using Agglomerative Clustering
Remote Sensing, 2020 Many tasks in hyperspectral imaging, such as spectral unmixing and sub-pixel matching, require knowing how many substances or materials are present in the scene captured by a hyperspectral image.
José Prades +3 more
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