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Springer - Errors-in-Variables Methods in System Identification

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Description

Gain a deep understanding of system identification through this technical resource from Springer. This book provides a comprehensive overview of different errors-in-variables (EIV) methods, which are essential when your goal is to determine the physical laws that describe a specific process. Unlike methods focused solely on prediction or controlling future behavior, EIV approaches are designed for those seeking true physical insight into a process. Readers will examine the core properties of EIV problems and address the complex challenge of model parameter identifiability. Because identifying parameters in EIV scenarios is a non-trivial task, this text explores the sufficient conditions required for successful identifiability. This book serves as a specialized guide for researchers and engineers working within communications and control engineering who require mathematical accuracy to model physical systems effectively.

Key Features

Comprehensive overview of different errors-in-variables (EIV) methods used for effective system identification.

Focus on determining physical laws to provide deep insight into how a process functions.

Detailed exploration of the properties inherent in EIV problems for technical modeling.

Analysis of model parameter identifiability and the sufficient conditions required for success.

Targeted content designed for professionals in communications and control engineering.

Product Specifications

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

Barcode

No barcode data available

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