Discrete Stochastic Processes and Optimal Filtering

Concerned with the founding principles of optimal filters, this volume presents several reminders about both random vectors and Gaussian vectors. The study of discrete time processes allow readers to tackle digital filtering, while a chapter on estimation gives the principle results necessary for the construction of the Wiener filter and of the adaptive filter used in the case of stationary signals. It concludes with an examination of Kalman filtering, which extends optimal filtering to the case of non-stationary signals. Exercises with solutions punctuate each chapter, and practical examples are given using Matlab software.

Summary

Optimal filtering applied to stationary and non-stationary signals provides the most efficient means of dealing with problems arising from the extraction of noise signals. Moreover, it is a fundamental feature in a range of applications, such as in navigation in aerospace and aeronautics, filter processing in the telecommunications industry, etc.

Product details

• Authors: Jean-Claude Bertein, Roger Ceschi
• Assisted by: Jean-Claude Bertein (Editor), Roger Ceschi (Editor)
• Publisher: ISTE Ltd.
• Languages: English
• Product format: Hardback
• Released: 01.01.2007
• No. of pages: 302
• Dimensions: 164 mm x 238 mm x 21 mm
• Weight: 586 g
• Series: Digital Signal and Image Proce
• Subject: Natural sciences, medicine, IT, technology > Mathematics > Miscellaneous