Téléchargez le livre : Low Rank Approximation

Low Rank Approximation

Algorithms, Implementation, Applications de

Éditeur :

Springer


Collection :

Communications and Control Engineering

Paru le : 2011-11-19

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Description
Data Approximation by Low-complexity Models details the theory, algorithms, and applications of structured low-rank approximation. Efficient local optimization methods and effective suboptimal convex relaxations for Toeplitz, Hankel, and Sylvester structured problems are presented. Much of the text is devoted to describing the applications of the theory including: system and control theory; signal processing; computer algebra for approximate factorization and common divisor computation; computer vision for image deblurring and segmentation; machine learning for information retrieval and clustering; bioinformatics for microarray data analysis; chemometrics for multivariate calibration; and psychometrics for factor analysis. Software implementation of the methods is given, making the theory directly applicable in practice. All numerical examples are included in demonstration files giving hands-on experience and exercises and MATLAB® examples assist in the assimilation of the theory.
Pages
258 pages
Collection
Communications and Control Engineering
Parution
2011-11-19
Marque
Springer
EAN papier
9781447122265
EAN EPUB
9781447122272
Informations sur l'ebook
Nombre pages copiables
2
Nombre pages imprimables
25
Taille du fichier
5591 Ko
Prix
116,04 €

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