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Non-negative Matrix Factorization Techniques [electronic resource] : Advances in Theory and Applications / edited by Ganesh R. Naik.

Contributor(s): Naik, Ganesh R [editor.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Signals and Communication Technology: Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2016Edition: 1st ed. 2016.Description: VII, 194 p. 53 illus., 24 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783662483312.Subject(s): Engineering | Artificial intelligence | Computer graphics | Computer mathematics | Biomedical engineering | Engineering | Signal, Image and Speech Processing | Computer Imaging, Vision, Pattern Recognition and Graphics | Computational Mathematics and Numerical Analysis | Artificial Intelligence (incl. Robotics) | Biomedical EngineeringAdditional physical formats: Printed edition:: No titleDDC classification: 621.382 Online resources: Click here to access online
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.
In: Springer eBooksSummary: 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.
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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.

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