Optimal Filtering in Signal Processing

Optimal filtering applied to stationary and non-stationary signals offers the most efficient means of addressing noise extraction problems. It is a fundamental feature in various applications, including navigation in aerospace and aeronautics, and filter processing in the telecommunications industry.

This book provides a comprehensive overview of this area, discussing random and Gaussian vectors, outlining the results necessary for the creation of Wiener and adaptive filters used for stationary signals, and examining Kalman filters which are used in relation to non-stationary signals. Exercises with solutions are included in each chapter to demonstrate the practical application of these ideas using MATLAB.