System Identification

Electrical Engineering System Identification A Frequency Domain Approach How does one model a linear dynamic system from noisy data? This book presents a general approach to this problem, with both practical examples and theoretical discussions that give the reader a sound understanding of the subject and of the pitfalls that might occur on the road from raw data to validated model. The emphasis is on robust methods that can be used with a minimum of user interaction.

Electrical Engineering System Identification A Frequency Domain Approach How does one model a linear dynamic system from noisy data?

An in-depth introduction to subspace methods for system identification in discrete-time linear systems thoroughly augmented with advanced and novel results, this text is structured into three parts.

This is a textbook for graduate courses in discrete-time random processes, statistical signal processing, and blind equalization and system identification. This volume provides such a unified treatment presenting theory, performance analysis, simulation, implementation and applications.