Low-Rank Approximation Algorithms, Implementation, Applications /

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...

Full description

Bibliographic Details
Main Author: Markovsky, Ivan (Author)
Corporate Author: SpringerLink (Online service)
Format: e-Book
Language:English
Published: Cham : Springer International Publishing : Imprint: Springer, 2019.
Edition:2nd ed. 2019.
Series:Communications and Control Engineering,
Subjects:
Control engineering.
Robotics.
Automation.
System theory.
Control theory.
Computer science > Mathematics.
Mathematical models.
Artificial intelligence.
Signal processing.
Control, Robotics, Automation.
Systems Theory, Control.
Symbolic and Algebraic Manipulation.
Mathematical Modeling and Industrial Mathematics.
Artificial Intelligence.
Signal, Speech and Image Processing.
Online Access:Full-text access
View in OPAC
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. .

Similar Items