rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Low-Rank Approximation
    sub title: Algorithms, Implementation, Applications
  name:
    name part: Markovsky, Ivan.
    role:
      role term: creator
    role:
      role term: author.
    role:
      role term: aut
    role:
      role term: http://id.loc.gov/vocabulary/relators/aut
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2019
    edition: 2nd ed. 2019.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XIII, 272 p. 19 illus., 15 illus. in color. online resource.
  abstract: This 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.
  table of contents: Chapter 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 ﬁltering and control -- Chapter 7. Nonlinear modeling problems -- Chapter 8. Dealing with prior knowledge -- Index. .
  note: by Ivan Markovsky.
  subject:
    topic: Control engineering
  subject:
    topic: Robotics
  subject:
    topic: Mechatronics
  subject:
    topic: System theory
  subject:
    topic: Computer science-Mathematics
  subject:
    topic: Mathematical models
  subject:
    topic: Artificial intelligence
  subject:
    topic: Signal processing
  subject:
    topic: Image processing
  subject:
    topic: Speech processing systems
  subject:
    topic: Control, Robotics, Mechatronics
  subject:
    topic: Systems Theory, Control
  subject:
    topic: Symbolic and Algebraic Manipulation
  subject:
    topic: Mathematical Modeling and Industrial Mathematics
  subject:
    topic: Artificial Intelligence
  subject:
    topic: Signal, Image and Speech Processing
  classification: TJ210.2-211.495
  classification: TJ163.12
  classification: 629.8
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Communications and Control Engineering
  identifier: 9783319896205
  identifier: https://doi.org/10.1007/978-3-319-89620-5
  record info:
    record creation date: 180803
    record change date: 20191024091743.0
    record identifier: 978-3-319-89620-5