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Springer Errors-in-Variables Methods in System Identification

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Description

This comprehensive guide explores errors-in-variables (EIV) methods for system identification, offering readers a thorough overview of different EIV approaches and their applications. The book examines the properties of EIV problems, which are essential when the goal is understanding the physical laws governing a process rather than predicting or controlling future behaviour. EIV problems commonly arise in modelling work aimed at gaining physical insight into processes, making this resource particularly valuable for engineers and researchers working on identifiability challenges. The book addresses the non-trivial issue of model parameter identifiability in EIV contexts and provides sufficient conditions for determining when parameters can be reliably recovered from measured data containing errors.

Key Features

Presents a comprehensive overview of different errors-in-variables methods used in system identification problems.

Explores the mathematical properties and characteristics of EIV problems in process modelling and parameter estimation.

Addresses the identifiability of model parameters for errors-in-variables systems, a critical concern in system identification.

Focuses on physical insight and understanding of processes rather than prediction or control applications.

Published by Springer in the Communications and Control Engineering series, ensuring academic rigour and expert content.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
20 April 2018
Listed Since
28 December 2017

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