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Markovsky, Ivan 作者

Springer London Ltd

译者

2011-11 出版日期

266 页数

$ 123.17 价格

丛书系列

9781447122265 图书编码

Low Rank Approximation 在线电子书图书标签: 数学 system recommended

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Low Rank Approximation 在线电子书 epub 下载 mobi 下载 pdf 下载 txt 下载 2024

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Low Rank Approximation 在线电子书图书描述

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(R) examples assist in the assimilation of the theory.

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