Low Rank Approximation: Algorithms, Implementation, Applications (Communications and Control Engineering) - Hardcover
Synopsis
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.
"synopsis" may belong to another edition of this title.
About the Author
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.
From the Back Cover
Matrix low-rank approximation is intimately related to data modelling; a problem that arises frequently in many different fields. Low Rank Approximation: Algorithms, Implementation, Applications is a comprehensive exposition of the theory, algorithms, and applications of structured low-rank approximation. Local optimization methods and effective suboptimal convex relaxations for Toeplitz, Hankel, and Sylvester structured problems are presented. A major part of the text is devoted to application of the theory. Applications described include:
- system and control theory: approximate realization, model reduction, output error, and errors-in-variables identification;
- signal processing: harmonic retrieval, sum-of-damped exponentials, finite impulse response modeling, and array processing;
- machine learning: multidimensional scaling and recommender system;
- computer vision: algebraic curve fitting and fundamental matrix estimation;
- bioinformatics for microarray data analysis;
- chemometrics for multivariate calibration;
- psychometrics for factor analysis; and
- computer algebra for approximate common divisor computation.
Special knowledge from the respective application fields is not required. The book is complemented by a software implementation of the methods presented, which makes the theory directly applicable in practice. In particular, all numerical examples in the book are included in demonstration files and can be reproduced by the reader. This gives hands-on experience with the theory and methods detailed. In addition, exercises and MATLAB® examples will assist the reader quickly to assimilate the theory on a chapter-by-chapter basis.
Low Rank Approximation: Algorithms, Implementation, Applications is a broad survey of the theory and applications of its field which will be of direct interest to researchers in system identification, control and systems theory, numerical linear algebra and optimization. The supplementary problems and solutions render it suitable for use in teaching graduate courses in those subjects as well.
"About this title" may belong to another edition of this title.
Other Popular Editions of the Same Title
Search results for Low Rank Approximation: Algorithms, Implementation,...
Stock Image
Low Rank Approximation. Algorithms, Implementation, Applications.
Seller: Universitätsbuchhandlung Herta Hold GmbH, Berlin, Germany
Seller rating 5 out of 5 stars
64 illus., 55 in color., X, 256 p. Hardcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Stamped. Sprache: Englisch. Seller Inventory # 7360DB
Buy Used
US$ 20.53
US$ 35.18 shipping
Ships from Germany to U.S.A.
Ships from Germany to U.S.A.
Quantity: 1 available
Stock Image
Low Rank Approximation: Algorithms, Implementation, Applications (Communications and Control Engineering)
Seller: Anybook.com, Lincoln, United Kingdom
Seller rating 5 out of 5 stars
Condition: Fair. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In fair condition, suitable as a study copy. No dust jacket. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,600grams, ISBN:9781447122265. Seller Inventory # 4326450
Buy Used
US$ 39.99
US$ 17.94 shipping
Ships from United Kingdom to U.S.A.
Ships from United Kingdom to U.S.A.
Quantity: 1 available
Seller Image
Low Rank Approximation: Algorithms, Implementation, Applications (Communications and Control Engineering)
Published by
Springer-Verlag Publishing, 2011
ISBN 10: 1447122267
ISBN 13: 9781447122265
Used
Hardcover
Seller: Salish Sea Books, Bellingham, WA, U.S.A.
Seller rating 5 out of 5 stars
Condition: Very Good. Very Good++; Hardcover; Close to new condition; Covers are still glossy with "straight" edge-corners; Unblemished textblock edges; The endpapers and all text pages are bright and unmarked; Binding is tight with a straight spine; This book will be stored and delivered in a sturdy cardboard box with foam padding; Medium Format (8.5" - 9.75" tall); Red and blue covers with title in white lettering; 2011, Springer-Verlag Publishing; 258 pages; "Low Rank Approximation: Algorithms, Implementation, Applications (Communications and Control Engineering)," by Ivan Markovsky. Seller Inventory # SKU-U47BE15612197
Stock Image
Low Rank Approximation: Algorithms, Implementation, Applications (Communications and Control Engineering)
Seller: GoldBooks, Denver, CO, U.S.A.
Seller rating 5 out of 5 stars
Condition: new. Seller Inventory # 4X46_50_1447122267
Seller Image
Low Rank Approximation: Algorithms, Implementation, Applications (Communications and Control Engineering) : Algorithms, Implementation, Applications
Seller: AHA-BUCH GmbH, Einbeck, Germany
Seller rating 5 out of 5 stars
Gebundene Ausgabe. Condition: Neu. Neu neuware, importqualität, auf lager - 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. Seller Inventory # INF1000416208
Buy New
US$ 169.07
US$ 73.80 shipping
Ships from Germany to U.S.A.
Ships from Germany to U.S.A.
Quantity: 1 available
Seller Image
Low Rank Approximation: Algorithms, Implementation, Applications (Communications and Control Engineering) : Algorithms, Implementation, Applications
Seller: AHA-BUCH GmbH, Einbeck, Germany
Seller rating 5 out of 5 stars
Hardcover. Condition: Neu. Neu Neuware, Importqualität, auf Lager - 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. Matrix low-rank approximation is intimately related to data modelling by a linear system; a problem that arises frequently in many different fields. This book is a comprehensive exposition of 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. A major part of the text is devoted to application of the theory. Applications described include: system and control theory: approximate realization, model reduction, output error and errors-in-variables identification; signal processing: harmonic retrieval, sum-of-damped exponentials, finite impulse response modelling, and array 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.Special knowledge from the respective application fields is not required. The book is complemented by a software implementation of the methods presented, which makes the theory directly applicable in practice. In particular, all numerical examples in the book are included in demonstration files and can be reproduced by the reader. This gives hands-on experience with the theory and methods detailed. In addition, exercises and MATLAB® examples will assist the reader quickly to assimilate the theory on a chapter-by-chapter basis. Data Approximation by Low-complexity Models is a broad survey of the theory and applications of its field which will be of direct interest to researchers in system identification, control and systems theory, numerical linear algebra and optimization. The supplementary electronic lecture slides, problems and solutions render it suitable for use in teaching graduate courses in those subjects as well. The Communications and Control Engineering series reports major technological advances which have potential for great impact in the fields of communication and control. It reflects research in industrial and academic institutions around the world so that the readership can exploit new possibilities as they become available. Seller Inventory # INF1000770025
Buy New
US$ 180.90
US$ 73.80 shipping
Ships from Germany to U.S.A.
Ships from Germany to U.S.A.
Quantity: 1 available