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200 10$aLow-Rank Approximation $eAlgorithms, Implementation, Applications /$fby Ivan Markovsky
205   $a2nd ed. 2019.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2019.
215   $a1 online resource (280 pages)
225 1 $aCommunications and Control Engineering,$x0178-5354
311   $a3-319-89619-9 
327   $aChapter 1. Introduction -- Part I: Linear modeling problems -- Chapter 2. From data to models -- Chapter 3. Exact modelling -- Chapter 4. Approximate modelling -- Part II: Applications and generalizations -- Chapter 5. Applications -- Chapter 6. Data-driven ?ltering and control -- Chapter 7. Nonlinear modeling problems -- Chapter 8. Dealing with prior knowledge -- Index. .
330   $aThis book is a comprehensive exposition of the theory, algorithms, and applications of structured low-rank approximation. Local optimization methods and effective suboptimal convex relaxations for Toeplitz, Hankel, and Sylvester structured problems are presented. A major part of the text is devoted to application of the theory with a range of applications from systems and control theory to psychometrics being described. Special knowledge of the application fields is not required. The second edition of /Low-Rank Approximation/ is a thoroughly edited and extensively rewritten revision. It contains new chapters and sections that introduce the topics of: ? variable projection for structured low-rank approximation; ? missing data estimation; ? data-driven filtering and control; ? stochastic model representation and identification; ? identification of polynomial time-invariant systems; and ? blind identification with deterministic input model. The book is complemented by a software implementation of the methods presented, which makes the theory directly applicable in practice. In particular, all numerical examples in the book are included in demonstration files and can be reproduced by the reader. This gives hands-on experience with the theory and methods detailed. In addition, exercises and MATLAB^® /Octave examples will assist the reader quickly to assimilate the theory on a chapter-by-chapter basis. ?Each chapter is completed with a new section of exercises to which complete solutions are provided.? Low-Rank Approximation (second edition) is a broad survey of the Low-Rank Approximation theory and applications of its field which will be of direct interest to researchers in system identification, control and systems theory, numerical linear algebra and optimization. The supplementary problems and solutions render it suitable for use in teaching graduate courses in those subjects as well.
410  0$aCommunications and Control Engineering,$x0178-5354
606   $aControl engineering
606   $aRobotics
606   $aMechatronics
606   $aSystem theory
606   $aComputer science?Mathematics
606   $aMathematical models
606   $aArtificial intelligence
606   $aSignal processing
606   $aImage processing
606   $aSpeech processing systems
606   $aControl, Robotics, Mechatronics$3https://scigraph.springernature.com/ontologies/product-market-codes/T19000
606   $aSystems Theory, Control$3https://scigraph.springernature.com/ontologies/product-market-codes/M13070
606   $aSymbolic and Algebraic Manipulation$3https://scigraph.springernature.com/ontologies/product-market-codes/I17052
606   $aMathematical Modeling and Industrial Mathematics$3https://scigraph.springernature.com/ontologies/product-market-codes/M14068
606   $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000
606   $aSignal, Image and Speech Processing$3https://scigraph.springernature.com/ontologies/product-market-codes/T24051
615  0$aControl engineering.
615  0$aRobotics.
615  0$aMechatronics.
615  0$aSystem theory.
615  0$aComputer science?Mathematics.
615  0$aMathematical models.
615  0$aArtificial intelligence.
615  0$aSignal processing.
615  0$aImage processing.
615  0$aSpeech processing systems.
615 14$aControl, Robotics, Mechatronics.
615 24$aSystems Theory, Control.
615 24$aSymbolic and Algebraic Manipulation.
615 24$aMathematical Modeling and Industrial Mathematics.
615 24$aArtificial Intelligence.
615 24$aSignal, Image and Speech Processing.
676   $a511.42
700   $aMarkovsky$b Ivan$4aut$4http://id.loc.gov/vocabulary/relators/aut$0771248
906   $aBOOK
912   $a9910483444103321
996   $aLow rank approximation$91573750
997   $aUNINA