Discrete-time Stochastic Systems: Estimation And Control (Advanced Textbooks in Control and Signal Processing) - Softcover

Über die Autorin bzw. den Autor

Torsten Söderström received a PhD degree in automatic control in 1973, from Lund Institute of Technology, Sweden. He is a Life Fellow of IEEE, and an IFAC Fellow. Since 1974, he has been with the Division of Systems and Control at Uppsala University, where he is now a professor emeritus of automatic control. His main research interests are in the fields of system identification and estimation. In these areas he has published numerous papers, and is the co-author of four books. In 1981 he was given an Automatica Paper Prize Award along with other co-authors. He has been the Automatica editor for the area of system identification since 1992.

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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 posteriori 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 mayalso be of assistance for self study and as a reference.