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Modified singular value decomposition by means of independent component analysis

V.D. Vrabie, J.I. Mars, J.-L. Lacoume
2004 Signal Processing  
To relax this condition, exploiting the concept of Independent Component Analysis (ICA), we propose another orthogonal matrix made up of statistically independent normalized wavelets.  ...  The Singular Value Decomposition (SVD) is a useful tool to achieve this separation. It provides two orthogonal matrices that convey information on normalized wavelets and propagation vectors.  ...  Based on the assumption that s 1 (n) is independent from the other source waves, this can be achieved by the Independent Component Analysis (ICA).  ... 
doi:10.1016/j.sigpro.2003.12.007 fatcat:c6vso7qpgreqxnfbkqvnkqg2w4

Modified singular spectrum analysis in identifying rainfall trend over peninsular Malaysia

S.M. Shaharudin, N. Ahmad, N.H. Zainuddin
2019 Indonesian Journal of Electrical Engineering and Computer Science  
<p>Identifying the local time scale of the torrential rainfall pattern through Singular Spectrum Analysis (SSA) is useful to separate the trend and noise components.  ...  However, SSA poses two main issues which are torrential rainfall time series data have coinciding singular values and the leading components from eigenvector obtained from the decomposing time series matrix  ...  Modified SSA help to move apart decomposition components where it would refined groups by using Robust Sparse K-Means (RSK-means) and grouping results of the components can be supported by eigenvector  ... 
doi:10.11591/ijeecs.v15.i1.pp283-293 fatcat:gnkolnxaknf2xmjewwwcfg2e3i

Sparse Distributed Representations for Words with Thresholded Independent Component Analysis

Jaakko J. Vayrynen, Lasse Lindqvist, Timo Honkela
2007 Neural Networks (IJCNN), International Joint Conference on  
The applicability of the thresholded ICA representation is compared to singular value decomposition (SVD) in a multiple choice vocabulary task with three data sets.  ...  We show that independent component analysis (ICA) can be used to find distributed representations for words that can be further processed by thresholding to produce sparse representations.  ...  ACKNOWLEDGMENT This work was supported in part by the Helsinki Graduate School of Computer Science and Engineering, the Academy of Finland through the Finnish Centre of Excellence Programme and Nokia Foundation  ... 
doi:10.1109/ijcnn.2007.4371100 dblp:conf/ijcnn/VayrynenLH07 fatcat:dcquinsmk5cxvjws6qdvowvwfm

Spectral analysis of signals by Root-Min-Norm method, using modified SSA method

В.І. Василишин
2018 Системи обробки інформації  
The paper considers the problem of efficiency enhancing of spectral analysis of the signals observed against noise via Root-Min-Norm method with data preprocessing by modification of the SSA method.  ...  Simulations results are presented that confirm the enhancement of spectral analysis efficiency by Root-Min-Norm method when using the SSA method and its modification.  ...  The eigenvalue decomposition (EVD) of the CM of observations or singular value decomposition of the data matrix is the base of the modern spectral analysis methods.  ... 
doi:10.30748/soi.2018.152.02 fatcat:l4ceph7ftbdb5dryjzabdoetty

A Single Number Index to Assess Selected Acoustic Parameters in Churches with Redundant Information

Krzysztof Kosała
2011 Archives of Acoustics  
The formula is created by means of the Singular Value Decomposition (SVD) method.  ...  The new procedures for calculating the values of three partial indices and the single number index to assess selected acoustic parameters are presented.  ...  Acknowledgment The project has been performed within the statutory works of the Department of Mechanics and Vibroacoustics of AGH -2010-2013, No. 3: "Prediction and experimental research of the new structures  ... 
doi:10.2478/v10168-011-0039-3 fatcat:hjizjrhsnjh5rmdxxyowtisixm

Comparison of different methods for the derivation of the vectorcardiogram from the ECG and morphology descriptors

J.A. Belloch, M.S. Guillem, A. Climent, J. Millet, D. Husser, A. Bollman
2007 2007 Computers in Cardiology  
Vectorcardiograms were reconstructed for 180 patients by applying Singular Value Decomposition and Dower's inverse transform.  ...  Also, low correlation values were found among any of the morphological parameters under evaluation.  ...  Acknowledgements This work was partially supported by the grants UPV, ENFASIS-TEC2005-08401 (Spain) and the Volkswagen Foundation (Germany).  ... 
doi:10.1109/cic.2007.4745515 fatcat:na2ohgucgfemtmvqz4culaxn7m

Gabased Digital Image Watermarking For Enhanced Robustness and Imperceptibility

R. Surya Prakasa Rao, Dr. P. Rajesh Kumar
2017 IOSR Journal of Computer Engineering  
The singular values of the watermark are embedded in a detail sub-band of host image after third level approximation.  ...  In this paper an optimal watermarking scheme based on singular value decomposition (SVD) and Discrete wavelet transform (DWT) using multi-objective genetic algorithm (GA) optimization is presented.  ...  (vii) Modify the singular value of I G by embedding singular value of W G in LL sub band and for remaining such that 3 = 3 + * ,where = , , , .  ... 
doi:10.9790/0661-1903012633 fatcat:xj3e4y5jnjaalovi2jv7gg2czu

Symplectic geometry spectrum analysis of nonlinear time series

H.-B. Xie, T. Guo, B. Sivakumar, A. W.-C. Liew, S. Dokos
2014 Proceedings of the Royal Society A  
Various time-series decomposition techniques, including wavelet transform, singular spectrum analysis, empirical mode decomposition and independent component analysis, have been developed for nonlinear  ...  In this paper, we describe a symplectic geometry spectrum analysis (SGSA) method to decompose a time series into a set of independent additive components.  ...  Distinct from the above techniques, SSA uses singular value decomposition (SVD) to reshape a time series into a sum of independent and interpretable components, such as a slowly [3] .  ... 
doi:10.1098/rspa.2014.0409 fatcat:wtfjrr5g4bg37oipthycem2me4

Pure component spectral recovery and constrained matrix factorizations: concepts and applications

Klaus Neymeyr, Mathias Sawall, Dieter Hess
2010 Journal of Chemometrics  
For strongly overlapping spectra a penalty condition on a specific singular value of the absorptivity matrix factor and a global decomposition approach are appropriate tools to construct improved factorizations  ...  The usefulness of the method is demonstrated and compared with established tools for model problems and for a system from catalytic hydroformylation by Rhodium complexes both with overlapping component  ...  A = CÂ, then a reconstruction of C and can be recovered only from A by means of the singular value decomposition.  ... 
doi:10.1002/cem.1273 fatcat:ttzdy4vcdvcetm6rupq4swj3oa

The Centroid Decomposition: Relationships between Discrete Variational Decompositions and SVDs

Moody T. Chu, Robert E. Funderlic
2002 SIAM Journal on Matrix Analysis and Applications  
The centroid decomposition, an approximation for the singular value decomposition (SVD), has a long history among the statistics/psychometrics community for factor analysis research.  ...  One major purpose of this work is to show fundamental relationships between the singular value, centroid, and semidiscrete decompositions.  ...  Decomposition Centroid Singular value Semidiscrete for each centroid value.  ... 
doi:10.1137/s0895479800382555 fatcat:amurlouclvdildwo53vhpj6qvu

Performance Analysis of Image Watermarking Using Contourlet Transform and Extraction Using Independent Component Analysis

S. Saju, G. Thirugnanam
2016 Journal of Computers  
according to DWT and then watermark is embedded in singular values obtained by applying SVD.To extract the watermark, ICA-ML is used, it has a novel characteristic is that it does not require the transformation  ...  In this paper, performance analysis of digital image watermarking using contourlet transform is proposed.  ...  Independent component analysis (ICA) is a novel statistical technique that aims at finding linear projections of the data that maximize their mutual independence.  ... 
doi:10.17706/jcp.11.3.258-265 fatcat:yemhhhsdkzefphww33xrjcwx4a

A New Method of Blind Source Separation Using Single-Channel ICA Based on Higher-Order Statistics

Guangkuo Lu, Manlin Xiao, Ping Wei, Huaguo Zhang
2015 Mathematical Problems in Engineering  
Methods of utilizing independent component analysis (ICA) give little guidance about practical considerations for separating single-channel real-world data, in which most of them are nonlinear, nonstationary  ...  In the first step, the measured signal which is assumed to be piecewise higher order stationary time series is introduced and divided into a series of higher order stationary segments by applying a modified  ...  Acknowledgments This work was supported by the National Natural Science Foundation of China (61201282) and the Fundamental Research Funds for the Central Universities of China (no. ZYGX2013J016).  ... 
doi:10.1155/2015/439264 fatcat:kfmuzhtkxrei3jyhth5vfzxwym

Matrix factorisation methods applied in microarray data analysis

Andrew V. Kossenkov, Michael F. Ochs
2010 International Journal of Data Mining and Bioinformatics  
Broadly speaking, these methods define a series of mathematical approaches to matrix factorization with different approaches to the fitting of the model to the data.  ...  Here, we review several methods that have been developed that are capable of identifying patterns of behavior in transcriptional response and assigning genes to multiple patterns.  ...  Acknowledgments The authors wish to acknowledge funding from the National Library of Medicine (LM009382, LM008932) and the Maryland Tobacco Restitution Fund.  ... 
doi:10.1504/ijdmb.2010.030968 pmid:20376923 pmcid:PMC2998896 fatcat:nhoq7fem65bk7ptjnxiwoqtpqe

SVD based Data Transformation Methods for Privacy Preserving Clustering

M. NagaLakshmi, K Sandhya Rani
2013 International Journal of Computer Applications  
Nowadays privacy issues are major concern for many government and other private organizations to delve important information from large repositories of data.  ...  and independent component analysis.  ...  Singular Value Decomposition Among the different methods in data mining, Singular Value Decomposition (SVD) is one of the familiar methods [12] .  ... 
doi:10.5120/13473-1157 fatcat:a737bkrllnft3mmqxzbhhtpxbi

An Efficient Reference Free Adaptive Learning Process for Speech Enhancement Applications

Girika Jyoshna, Md. Zia Ur Rahman, L. Koteswararao
2022 Computers Materials & Continua  
This paper addresses a new adaptive speech enhancement (ASE) method based on a modified version of singular spectrum analysis (MSSA).  ...  During the transmission of speech signals, several noise components contaminate the actual speech components.  ...  Conflicts of Interest: The authors declare that they have no conflicts of interest to report regarding the present study.  ... 
doi:10.32604/cmc.2022.020160 fatcat:64bpgowpkvgb7d7uti5jjom5ku
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