國立高雄大學圖資館 |

Language: English

Back

Non-negative matrix factorization te...

Naik, Ganesh R.

Non-negative matrix factorization techniquesadvances in theory and applications /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Non-negative matrix factorization techniquesedited by Ganesh R. Naik.
Reminder of title:	advances in theory and applications /
other author:	Naik, Ganesh R.
Published:	Berlin, Heidelberg :Springer Berlin Heidelberg :2016.
Description:	vii, 194 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Non-negative matrices.
Online resource:	http://dx.doi.org/10.1007/978-3-662-48331-2
ISBN:	9783662483312$q(electronic bk.)

Non-negative matrix factorization techniquesadvances 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$q(electronic bk.)

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

191044
Non-negative matrices.

LC Class. No.: QA188

Dewey Class. No.: 512.9434

Non-negative matrix factorization techniquesadvances in theory and applications /
LDR:02410nmm a2200349 a 4500 001 481683
003 DE-He213
005 20160722144614.0
006 m d
007 cr nn 008maaau
008 161007s2016 gw s 0 eng d
020 $a 9783662483312$q(electronic bk.)
020 $a 9783662483305$q(paper)
024 7 $a 10.1007/978-3-662-48331-2 $2 doi
035 $a 978-3-662-48331-2
040 $a GP $c GP
041 0 $a eng
050 4 $a QA188
072 7 $a TTBM $2 bicssc
072 7 $a UYS $2 bicssc
072 7 $a TEC008000 $2 bisacsh
072 7 $a COM073000 $2 bisacsh
082 0 4 $a 512.9434 $2 23
090 $a QA188 $b .N812 2016
245 0 0 $a Non-negative matrix factorization techniques $h [electronic resource] : $b advances in theory and applications / $c edited by Ganesh R. Naik.
260 $a Berlin, Heidelberg : $b Springer Berlin Heidelberg : $b Imprint: Springer, $c 2016.
300 $a vii, 194 p. : $b ill., digital ; $c 24 cm.
490 1 $a Signals and communication technology, $x 1860-4862
505 0 $a 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.
520 $a 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.
650 0 $a Non-negative matrices. $3 191044
650 0 $a Matrices. $3 181876
650 0 $a Signal processing $x Mathematics. $3 183873
650 1 4 $a Engineering. $3 210888
650 2 4 $a Signal, Image and Speech Processing. $3 273768
650 2 4 $a Computer Imaging, Vision, Pattern Recognition and Graphics. $3 274492
650 2 4 $a Computational Mathematics and Numerical Analysis. $3 274020
650 2 4 $a Artificial Intelligence (incl. Robotics) $3 252959
650 2 4 $a Biomedical Engineering. $3 190464
700 1 $a Naik, Ganesh R. $3 681526
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer eBooks
830 0 $a Signals and communication technology. $3 557664
856 4 0 $u http://dx.doi.org/10.1007/978-3-662-48331-2
950 $a Engineering (Springer-11647)