Discrete-time Stochastic Systems

Estimation and Control

T. Söderström

376 pages, parution le 05/09/2002

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Résumé

Discrete-time Stochastic Systems gives a comprehensive introduction to the estimation and control of dynamic stochastic systems and provides complete derivations of key results such as the basic relations for Wiener filtering. The book covers both state-space methods and those based on the polynomial approach. Similarities and differences between these approaches are highlighted. Some non-linear aspects of stochastic systems (such as the bispectrum and extended Kalman filter) are also introduced and analysed. The books chief features are as follows: inclusion of the polynomial approach provides alternative and simpler computational methods than simple reliance on state-space methods; algorithms for analysis and design of stochastic systems allow for ease of implementation and experimentation by the reader; the highlighting of spectral factorization gives appropriate emphasis to this key concept often overlooked in the literature; explicit solutions of Wiener problems are handy schemes, well suited for computations compared with more commonly available but abstract formulations; complex-valued models that are directly applicable to many problems in signal processing and communications. Changes in the second edition include: additional information covering spectral factorisation and the innovations form; the chapter on optimal estimation being completely rewritten to focus on a posterior estimates rather than maximum likelihood; new material on fixed lag smoothing and algorithms for solving Riccati equations are improved and more up to date; new presentation of polynomial control and new derivation of linear-quadratic-Gaussian control. Discrete-time Stochastic Systems is primarily of benefit to students taking M.Sc. courses in stochastic estimation and control, electronic engineering and signal processing but may also be of assistance for self study and as a reference.

Contents

Introduction
Some Probability Theory
Models
Analysis
Optimal Estimation
Optimal State Estimation for Linear Systems
Optimal Estimation for Linear Systems by Polynomial Methods
Illustration of Optimal Linear Estimation
Non-linear Filtering
Introduction to Optimal Stochastic Control
Linear Quadratic Gaussian Control
Answers to Selected Problems

L'auteur - T. Söderström

Söderström, T., University of Uppsala, Sweden

Caractéristiques techniques

	PAPIER
Éditeur(s)	Springer
Auteur(s)	T. Söderström
Parution	05/09/2002
Nb. de pages	376
Format	15,5 x 23,5
Couverture	Broché
Poids	603g
Intérieur	Noir et Blanc
EAN13	9781852336493
ISBN13	978-1-85233-649-3