Overview
- Covers the latest cutting edge topics on NMF and emphasis on open problems on NMF
- Balance on both theory and applications with examples
- Offers in-depth analysis of NMF topics simply not covered elsewhere
- Includes most advanced and popular areas of NMF, Also, focuses to broad and comprehensive description of all the core principles of NMF
- Includes supplementary material: sn.pub/extras
Part of the book series: Signals and Communication Technology (SCT)
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Table of contents (8 chapters)
Keywords
About this book
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.
Editors and Affiliations
Bibliographic Information
Book Title: Non-negative Matrix Factorization Techniques
Book Subtitle: Advances in Theory and Applications
Editors: Ganesh R. Naik
Series Title: Signals and Communication Technology
DOI: https://doi.org/10.1007/978-3-662-48331-2
Publisher: Springer Berlin, Heidelberg
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2016
Hardcover ISBN: 978-3-662-48330-5Published: 05 October 2015
Softcover ISBN: 978-3-662-51700-0Published: 23 August 2016
eBook ISBN: 978-3-662-48331-2Published: 25 September 2015
Series ISSN: 1860-4862
Series E-ISSN: 1860-4870
Edition Number: 1
Number of Pages: VII, 194
Topics: Signal, Image and Speech Processing, Computer Imaging, Vision, Pattern Recognition and Graphics, Computational Mathematics and Numerical Analysis, Artificial Intelligence, Biomedical Engineering and Bioengineering