Publisher Description

Random Signals, Noise and Filtering develops the theory of random processes and its application to the study of systems and analysis of random data. The text covers three important areas: (1) fundamentals and examples of random process models, (2) applications of probabilistic models: signal detection, and filtering, and (3) statistical estimation--measurement and analysis of random data to determine the structure and parameter values of probabilistic models. This volume by Breipohl and Shanmugan offers the only one-volume treatment of the fundamentals of random process models, their applications, and data analysis.

Author Biography

K. Sam Shanmugan and Arthur M. Breipohl are the authors of Random Signals: Detection, Estimation and Data Analysis, published by Wiley.

Table of Contents

Preface and Introduction.

Review of Probability and Random Variables.

Random Processes and Sequences.

Response of Systems to Random Inputs.

Special Classes of Random Processes.

Signal Detection.

Linear Minimum MSE Filtering.

Statistics.

Estimating Parameters of Random Processes from Data.

Appendices.

Details