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System Identification with Quantized Observations

This book presents recently developed methodologies that utilize quantized information in system identification and explores their potential in extending control capabilities for systems with limited sensor information or networked systems. The results of these methodologies can be applied to signal...

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Bibliographic Details
Main Authors: Wang, Le Yi, Yin, G. George (Author), Zhang, Ji-Feng (Author), Zhao, Yanlong (Author)
Format: eBook
Language:English
Published: Boston, MA Birkhäuser 2010, 2010
Edition:1st ed. 2010
Series:Systems & Control: Foundations & Applications
Subjects:
Algorithms
Control And Systems Theory
Control Theory
Probability Theory
Systems Theory, Control
System Theory
Control Engineering
Telecommunication
Mathematical Modeling And Industrial Mathematics
Communications Engineering, Networks
Probabilities
Mathematical Models
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
Table of Contents:
  • Overview
  • System Settings
  • Stochastic Methods for Linear Systems
  • Empirical-Measure-Based Identification: Binary-Valued Observations
  • Estimation Error Bounds: Including Unmodeled Dynamics
  • Rational Systems
  • Quantized Identification and Asymptotic Efficiency
  • Input Design for Identification in Connected Systems
  • Identification of Sensor Thresholds and Noise Distribution Functions
  • Deterministic Methods for Linear Systems
  • Worst-Case Identification under Binary-Valued Observations
  • Worst-Case Identification Using Quantized Observations
  • Identification of Nonlinear and Switching Systems
  • Identification of Wiener Systems with Binary-Valued Observations
  • Identification of Hammerstein Systems with Quantized Observations
  • Systems with Markovian Parameters
  • Complexity Analysis
  • Space and Time Complexities, Threshold Selection, Adaptation
  • Impact of Communication Channels on System Identification

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