Low Rank Approximation: Algorithms, Implementation, Applications

Author:   Ivan Markovsky
Publisher:   Springer London Ltd
Edition:   2012
ISBN:  

9781447122265


Pages:   258
Publication Date:   19 November 2011
Replaced By:   9783319896199
Format:   Hardback
Availability:   Awaiting stock   Availability explained


Our Price $287.76 Quantity:  
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Low Rank Approximation: Algorithms, Implementation, Applications


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Author:   Ivan Markovsky
Publisher:   Springer London Ltd
Imprint:   Springer London Ltd
Edition:   2012
Dimensions:   Width: 15.50cm , Height: 1.80cm , Length: 23.50cm
Weight:   0.567kg
ISBN:  

9781447122265


ISBN 10:   1447122267
Pages:   258
Publication Date:   19 November 2011
Audience:   Professional and scholarly ,  Professional & Vocational
Replaced By:   9783319896199
Format:   Hardback
Publisher's Status:   Out of Print
Availability:   Awaiting stock   Availability explained

Table of Contents

Introduction.- From Data to Models.- Applications in System and Control Theory.- Applications in Signal Processing.- Applications in Computer Algebra.- Applications in Machine Learing.- Subspace-type Algorithms.- Algorithms Based on Local Optimization.- Data Smoothing and Filtering.- Recursive Algorithms.

Reviews

From the reviews: This is a carefully-elaborated monographic work on low rank approximation. It covers the state of the art in this field (key theoretical topics accompanied by the description of the associated algorithms) and discusses various classes of applications. The book provides a rigorous and self-contained material, including numerical examples implemented in MATLAB and a collection of relevant problems. The exposition corresponds to a postgraduate level. (Octavian Pastravanu, Zentralblatt MATH, Vol. 1245, 2012)


Author Information

Dr. Ivan Markovsky completed his PhD in the Electrical Engineering Department of the Katholieke Universiteit Leuven, Belgium under the supervision of S. Van Huffel, B. De Moor, and J.C. Willems. He was a postdoctoral researcher at the same department, and since January 2007, he has been a lecturer at the School of Electronics and Computer Science of the University of Southampton. His research interests are in system identification in the behavioural setting, total least squares, errors-in-variables estimation, and data-driven control; topics on which he has published 23 journal papers and one monograph (with SIAM). Dr. Markovsky won Honorable Mention in the Alston Householder Prize for best dissertation in numerical linear algebra. He is a co-organiser of the Fourth International Workshop on Total Least Squares and Errors-in-Variables Modelling, a guest editor of Signal Processing for a special issue on total least squares, and an associate editor of the International Journal of Control.

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