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Random Processes: Filtering, Estimation, and Detection

Random Processes: Filtering, Estimation, and Detection

Lonnie C. Ludeman

ISBN: 978-0-471-25975-6

Jan 2003, Wiley-IEEE Press

632 pages

Select type: Hardcover

In Stock



An understanding of random processes is crucial to many engineering fields-including communication theory, computer vision, and digital signal processing in electrical and computer engineering, and vibrational theory and stress analysis in mechanical engineering. The filtering, estimation, and detection of random processes in noisy environments are critical tasks necessary in the analysis and design of new communications systems and useful signal processing algorithms. Random Processes: Filtering, Estimation, and Detection clearly explains the basics of probability and random processes and details modern detection and estimation theory to accomplish these tasks.
In this book, Lonnie Ludeman, an award-winning authority in digital signal processing, joins the fundamentals of random processes with the standard techniques of linear and nonlinear systems analysis and hypothesis testing to give signal estimation techniques, specify optimum estimation procedures, provide optimum decision rules for classification purposes, and describe performance evaluation definitions and procedures for the resulting methods. The text covers four main, interrelated topics:

* Probability and characterizations of random variables and random processes
* Linear and nonlinear systems with random excitations
* Optimum estimation theory including both the Wiener and Kalman Filters
* Detection theory for both discrete and continuous time measurements

Lucid, thorough, and well-stocked with numerous examples and practice problems that emphasize the concepts discussed, Random Processes: Filtering, Estimation, and Detection is an understandable and useful text ideal as both a self-study guide for professionals in the field and as a core text for graduate students.

Preface xv

1 Experiments and Probability 1

2 Random Variables 37

3 Estimation of Random Variables 133

4 Random Processes 179

5 Linear Systems: Random Processes 247

6 Nonlinear Systems: Random Processes 295

7 Optimum Linear Filters: The Wiener Approach 335

8 Optimum Linear Systems: The Kalman Approach 383

9 Detection Theory: Discrete Observation 423

10 Detection Theory: Continuous Observation 511


Index 599

"The reader will find an excellent presentation ranging from the basic concepts of probability theory to the advanced topics of RP, filtering, estimation and detection." (IIE Transactions on Operations Engineering)