Errors-in-Variables Methods in System Identification

The book finds solutions that are constituted of methods that are compatible with a set of noisy data, which traditional approaches to solutions, such as (total) least squares, do not find. A number of identification methods for the EIV problem are presented. Each method is accompanied with a detail...

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Bibliographic Details
Main Author: Söderström, Torsten
Format: eBook
Language:English
Published: Cham Springer International Publishing 2018, 2018
Edition:1st ed. 2018
Series:Communications and Control Engineering
Subjects:
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
Table of Contents:
  • Chapter 1. Introduction
  • Chapter 2. The Static Case
  • Chapter 3. The Errors-in-Variables Problem for Dynamic Systems
  • Chapter 4. Identifiability Aspects
  • Chapter 5. Modeling Aspects
  • Chapter 6. Elementary Methods
  • Chapter 7. Methods Based on Bias-Compensation
  • Chapter 8. Covariance Matching
  • Chapter 9. Prediction Error and Maximum Likelihood Methods
  • Chapter 10. Frequency Domain Methods
  • Chapter 11. Total Least Squares
  • Chapter 12. Methods for Periodic Data
  • Chapter 13. Algorithmic Properties
  • Chapter 14. Asymptotic Distributions
  • Chapter 15. Errors-in-Variables Problems in Practice
  • Index
  • References