Random Processes: Filtering, Estimation, and Detection (Hardcover)
Lonnie C. Ludeman
- 出版商: Wiley-IEEE Press
- 出版日期: 2003-01-06
- 售價: $1,190
- 貴賓價: 9.8 折 $1,166
- 語言: 英文
- 頁數: 632
- 裝訂: Hardcover
- ISBN: 0471259756
- ISBN-13: 9780471259756
貴賓價: $998Fundamentals of Data Structures in C++
貴賓價: $970Introduction to Algorithms, 2/e
貴賓價: $1,007C How to Program, 4/e
貴賓價: $2,214Data Mining: Concepts and Techniques
貴賓價: $998Operating System Concepts, 6/e (Windows XP Update)
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.
Table of Contents
Experiments and Probability.
Estimation of Random Variables.
Linear Systems: Random Processes.
Nonlinear Systems: Random Processes.
Optimum Linear Filters: The Wiener Approach.
Optimum Linear Systems: The Kalman Approach.
Detection Theory: Discrete Observation.
Detection Theory: Continuous Observation.
Appendix A. The Bilateral Laplace Transform.
Appendix B. Table of Binomial Probabilities.
Appendix C. Table of Discrete Random Variables and Properties.
Appendix D. Table of Continuous Random Variables and Properties.
Appendix E. Table of Gaussian Cumulative Distribution Function.