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Non-negative matrix factorization techniques[electronic resource] :advances in theory and applications /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
杜威分類號:	512.9434
書名/作者:	Non-negative matrix factorization techniques : advances in theory and applications // edited by Ganesh R. Naik.
其他作者:	Naik, Ganesh R.
出版者:	Berlin, Heidelberg : : Springer Berlin Heidelberg :, 2016.
面頁冊數:	vii, 194 p. : : ill., digital ;; 24 cm.
Contained By:	Springer eBooks
標題:	Non-negative matrices.
標題:	Matrices.
標題:	Signal processing - Mathematics.
標題:	Engineering.
標題:	Signal, Image and Speech Processing.
標題:	Computer Imaging, Vision, Pattern Recognition and Graphics.
標題:	Computational Mathematics and Numerical Analysis.
標題:	Artificial Intelligence (incl. Robotics)
標題:	Biomedical Engineering.
ISBN:	9783662483312
ISBN:	9783662483305
內容註:	From Binary NMF to Variational Bayes NMF: A Probabilistic Approach -- Non Negative Matrix Factorizations for Intelligent Data Analysis -- Automatic extractive multi-document summarization based on Archetypal Analysis -- Bounded Matrix Low Rank Approximation -- A Modified NMF-based Filter Bank Approach for Enhancement of Speech Data in Non-stationary Noise -- Separation of stellar spectra based on non-negativity and parametric modelling of mixing operator -- NMF in MR Spectroscopy -- Time-Scale Based Segmentation for Degraded PCG Signals Using NMF.
摘要、提要註:	This book collects new results, concepts and further developments of NMF. The open problems discussed include, e.g. in bioinformatics: NMF and its extensions applied to gene expression, sequence analysis, the functional characterization of genes, clustering and text mining etc. The research results previously scattered in different scientific journals and conference proceedings are methodically collected and presented in a unified form. While readers can read the book chapters sequentially, each chapter is also self-contained. This book can be a good reference work for researchers and engineers interested in NMF, and can also be used as a handbook for students and professionals seeking to gain a better understanding of the latest applications of NMF.
電子資源:	http://dx.doi.org/10.1007/978-3-662-48331-2

Non-negative matrix factorization techniques[electronic resource] :advances in theory and applications /
Non-negative matrix factorization techniquesadvances in theory and applications /[electronic resource] :edited by Ganesh R. Naik. - Berlin, Heidelberg :Springer Berlin Heidelberg :2016. - vii, 194 p. :ill., digital ;24 cm. - Signals and communication technology,1860-4862. - Signals and communication technology..

From Binary NMF to Variational Bayes NMF: A Probabilistic Approach -- Non Negative Matrix Factorizations for Intelligent Data Analysis -- Automatic extractive multi-document summarization based on Archetypal Analysis -- Bounded Matrix Low Rank Approximation -- A Modified NMF-based Filter Bank Approach for Enhancement of Speech Data in Non-stationary Noise -- Separation of stellar spectra based on non-negativity and parametric modelling of mixing operator -- NMF in MR Spectroscopy -- Time-Scale Based Segmentation for Degraded PCG Signals Using NMF.

This book collects new results, concepts and further developments of NMF. The open problems discussed include, e.g. in bioinformatics: NMF and its extensions applied to gene expression, sequence analysis, the functional characterization of genes, clustering and text mining etc. The research results previously scattered in different scientific journals and conference proceedings are methodically collected and presented in a unified form. While readers can read the book chapters sequentially, each chapter is also self-contained. This book can be a good reference work for researchers and engineers interested in NMF, and can also be used as a handbook for students and professionals seeking to gain a better understanding of the latest applications of NMF.

ISBN: 9783662483312

Standard No.: 10.1007/978-3-662-48331-2doiSubjects--Topical Terms:

495893
Non-negative matrices.

LC Class. No.: QA188

Dewey Class. No.: 512.9434

Non-negative matrix factorization techniques[electronic resource] :advances in theory and applications /
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