This book intends to provide graduate students in electrical and information science a solid background in stochastic signal processing. Chapter one introduces random signals through measurement noise. Chapter two develops fundamental concepts in probability theory and statistical methods. Chapter three is devoted to stochastic processes, stochastic system theory, and statistical signal processing. The examples are carefully selected. Some of them are aimed at motivating students interested in advanced topics such as signal detection, estimation, spectral analysis and system identification. Problems with solutions and MATLAB exercises are included to encourage self study by researchers or engineers in related areas.
The most important concepts in statistics are presented so that linear systems and nonlinear ones as rectifiers with random input and output signals have proper mathematical description and allow statistical inference. Such systems are fundamental to many engineering areas, for example, electronics, measurements, communications and control.