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...
Main Author: | |
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Format: | eBook |
Language: | English |
Published: |
Cham
Springer International Publishing
2018, 2018
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Edition: | 1st ed. 2018 |
Series: | Communications and Control Engineering
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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