Non-negative Matrix Factorization Techniques
Advances in Theory and Applications
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Beschreibung
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.
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.
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
Autor*in
Ganesh R. Naik
Themen in »Non-negative Matrix Factorization Techniques«
Blind Source Separation Multi-layer NMF Non-negative Matrix Factorisation (NMF) Pattern Recognition Simultaneous NMF Source Identification Source Separation Sparse Component Analysis Sparse Signal Time-frequency Signal