Full Product Details
Author: Ivan Markovsky
Publisher: Springer London Ltd
Imprint: Springer London Ltd
Edition: 2012 ed.
Dimensions:
Width: 15.50cm
, Height: 1.40cm
, Length: 23.50cm
Weight: 0.415kg
ISBN: 9781447158363
ISBN 10: 1447158369
Pages: 258
Publication Date: 26 January 2014
Audience:
College/higher education
,
Postgraduate, Research & Scholarly
Replaced By: 9783319896199
Format: Paperback
Publisher's Status: Active
Availability: Manufactured on demand
We will order this item for you from a manufactured on demand supplier.
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) This book gently takes the reader from the basic ideas of LRA to the most critical concepts, with an adequate number of examples to explain things along the way. ... Markovsky has presented LRA in a way that is unifying and cross-disciplinary. The pages abound with code, examples, applications, and problems, from which readers can pick according to their own interests and without the risk of losing the main thread of the book. ... it is a good reference for students, practitioners, and researchers. (Corrado Mencar, ACM Computing Reviews, December, 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.
