Signal and image processing is essentially the art of turning random information into understandable messages and pictures. An understanding of random processes is crucial in the study of many engineering systems. Filtering, estimation and detection underpins the ability to analyse and design new communications systems or image processing algorithms. In this book, Ludeman clearly explains the basics of probability and random processes, detailing modern detection and estimation theory.
Signal and image processing is essentially the art of turning random information into understandable messages and pictures. An understanding of random processes is crucial in the study of many engineering systems. Filtering, estimation and detection underpins the ability to analyse and design new communications systems or image processing algorithms. In this book, Ludeman clearly explains the basics of probability and random processes, detailing modern detection and estimation theory.
LONNIE C. LUDEMAN, PhD, received his doctorate from Arizona State University and is Professor Emeritus of electrical and computer engineering at New Mexico State University. In 1993, he was a Fulbright Scholar at the Aristotle University in Thessaloniki, Greece. He is the author of Fundamentals of Digital Signal Processing, which won Choice magazine's award for Outstanding Engineering Book of the Year.
Inhaltsangabe
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 Appendixes Index 599
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 Appendixes Index 599
Rezensionen
"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 )
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