Digital and Kalman Filtering An Introduction to Discrete-Time Filtering and Optimum Linear Estimation, Second Edition

This text for advanced undergraduates and graduate students provides a concise introduction to increasingly important topics in electrical engineering: digital filtering, filter design, and applications in the form of the Kalman and Wiener filters. The first half focuses on digital filtering, covering FIR and IIR filter design and other concepts. The second half addresses filtering noisy data to extract a signal, with chapters on nonrecursive (FIR Wiener) estimation, recursive (Kalman) estimation, and optimum estimation of vector signals.
The treatment is presented in tutorial form, but readers are assumed to be familiar with basic circuit theory, statistical averages, and elementary matrices. Central topics are developed gradually, including both worked examples and problems with solutions, and this second edition features new material and problems.

S. M. Bozic studied at Belgrade University and received his Ph.D. from the United Kingdom's University of Aston. He was a lecturer in the School of Electronic and Electrical Engineering at the University of Birmingham, and his other books include Electronic and Switching Circuits.

Preface to the first edition
Preface to the second edition
Part I: Digital filtering
Introduction
1. Introduction to discrete-time filtering
2. Digital filter characterization
3. FIR filter design
4. IIR filter design
5. Further concepts in discrete-time filtering
Part 2: Optimum (Wiener and Kalman) linear estimation
Introduction
6. Nonrecursive (FIR Wiener) estimation
7. Recursive (Kalman) estimation
8. Optimum estimation of vector signals
9. Examples
Solutions to problems
Appendix
References
Index