東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Non-negative matrix factorization te...

Naik, Ganesh R.

FindBook

Google Book

Amazon

博客來

Non-negative matrix factorization techniques = advances in theory and applications /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Non-negative matrix factorization techniques/ edited by Ganesh R. Naik.
其他題名:	advances in theory and applications /
其他作者:	Naik, Ganesh R.
出版者:	Berlin, Heidelberg :Springer Berlin Heidelberg : : 2016.,
面頁冊數:	vii, 194 p. :ill., digital ;24 cm.
內容註:	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.
Contained By:	Springer eBooks
標題:	Non-negative matrices. -
電子資源:	http://dx.doi.org/10.1007/978-3-662-48331-2
ISBN:	9783662483312$q(electronic bk.)

Non-negative matrix factorization techniques = advances 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:

646556
Non-negative matrices.

LC Class. No.: QA188

Dewey Class. No.: 512.9434

Non-negative matrix factorization techniques = advances in theory and applications /
LDR:02410nmm a2200349 a 4500 001 2029207
003 DE-He213
005 20160722144614.0
006 m d
007 cr nn 008maaau
008 160908s2016 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 646556
650 0 $a Matrices. $3 516894
650 0 $a Signal processing $x Mathematics. $3 579697
650 1 4 $a Engineering. $3 586835
650 2 4 $a Signal, Image and Speech Processing. $3 891073
650 2 4 $a Computer Imaging, Vision, Pattern Recognition and Graphics. $3 890871
650 2 4 $a Computational Mathematics and Numerical Analysis. $3 891040
650 2 4 $a Artificial Intelligence (incl. Robotics) $3 890894
650 2 4 $a Biomedical Engineering. $3 720279
700 1 $a Naik, Ganesh R. $3 2068411
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
830 0 $a Signals and communication technology. $3 1565543
856 4 0 $u http://dx.doi.org/10.1007/978-3-662-48331-2
950 $a Engineering (Springer-11647)