Non-negative Matrix Factorization Techniques: Advances in Theory and Applications

Author:   Ganesh R. Naik
Publisher:   Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Edition:   Softcover reprint of the original 1st ed. 2016
ISBN:  

9783662517000


Pages:   194
Publication Date:   23 August 2016
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Non-negative Matrix Factorization Techniques: Advances in Theory and Applications


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Overview

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.

Full Product Details

Author:   Ganesh R. Naik
Publisher:   Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Imprint:   Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Edition:   Softcover reprint of the original 1st ed. 2016
Weight:   3.168kg
ISBN:  

9783662517000


ISBN 10:   3662517000
Pages:   194
Publication Date:   23 August 2016
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

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.

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