Bayesian Bounds for Parameter Estimation and Nonlinear Filtering/Tracking
(Sprache: Englisch)
The first comprehensive development of Bayesian Bounds for parameter estimation and nonlinear filtering/tracking Bayesian estimation plays a central role in many signal processing problems encountered in radar, sonar, communications, seismology, and medical...
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The first comprehensive development of Bayesian Bounds for parameter estimation and nonlinear filtering/tracking Bayesian estimation plays a central role in many signal processing problems encountered in radar, sonar, communications, seismology, and medical diagnosis. There are often highly nonlinear problems for which analytic evaluation of the exact performance is intractable. A widely used technique is to find bounds on the performance of any estimator and compare the performance of various estimators to these bounds. This book provides a comprehensive overview of the state of the art in Bayesian Bounds. It addresses two related problems: the estimation of multiple parameters based on noisy measurements and the estimation of random processes, either continuous or discrete, based on noisy measurements. An extensive introductory chapter provides an overview of Bayesian estimation and the interrelationship and applicability of the various Bayesian Bounds for both static parameters and random processes. It provides the context for the collection of papers that are included. This book will serve as a comprehensive reference for engineers and statisticians interested in both theory and application. It is also suitable as a text for a graduate seminar or as a supplementary reference for an estimation theory course.
Bayesian Bounds provides a collection of the important papers dealing with the theory and application of Bayesian bounds. This book addresses two related problems: (1) the estimation of multiple parameters based on noisy measurements which arises frequently in radar, sonar, communication, seismology, and medical diagnosis AND (2) the estimation of a waveform, either discrete or continuous, based on noisy measurements. This edited volume uniquely provides a global perspective on bounds for parameter estimation from the benchmark journal articles scattered across the literature, with critical commentary and information that outlines the contributions of the selected paper and their interrelationship.
Autoren-Porträt
Harry L. Van Trees, ScD, is University Professor Emeritus at George Mason University. His career spans a variety of academic, government, and industry positions. He spent fourteen years as professor of electrical engineering at Massachusetts Institute of Technology. During this period he developed the three-volume series, Detection, Estimation, and Modulation Theory, which are the classical texts in the area and still widely used throughout the world. At George Mason University, he completed Part IV of the DEMT series, Optimum Array Processing. He served as chief scientist of the U.S. Air Force, principal deputy assistant secretary of defense for C3I, president of M/A-Com-Linkabit Government Systems, and founding director of the C3I Center at George Mason University. He is currently engaged in academic research at George Mason University, and is a consultant to several companies and government agencies.Kristine L. Bell, PhD, is Associate Professor in the Department of Statistics and C3I Center at George Mason University. In her doctoral thesis, she developed a significant generalization of the Ziv-Zakai bound that expanded its range of applicability. Her current research interests are in the areas of robust, adaptive signal processing techniques and performance bounds for source location and tracking with applications in radar, sonar, aeroacoustics, and satellite communications.
Bibliographische Angaben
- 2007, 1. Auflage., 968 Seiten, Maße: 28,3 cm, Gebunden, Englisch
- Ed. by Harry L. Van Trees and Kristine L. Bell
- Verlag: Wiley & Sons
- ISBN-10: 0470120959
- ISBN-13: 9780470120958
Sprache:
Englisch
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