Fundamentals of Statistical Processing: Estimation Theory, Volume 1: Estimation Theory, Volume 1 (Prentice-hall Signal Processing Series) - Hardcover

Kay, Steven; Kay, Steven M.

Hardcover

ISBN 10: 0133457117 ISBN 13: 9780133457117

Verlag: Pearson, 1993

Inhaltsangabe

A unified presentation of parameter estimation for those involved in the design and implementation of statistical signal processing algorithms. KEY TOPICS: Covers important approaches to obtaining an optimal estimator and analyzing its performance; and includes numerous examples as well as applications to real- world problems. MARKETS: For practicing engineers and scientists who design and analyze signal processing systems, i.e., to extract information from noisy signals ― radar engineer, sonar engineer, geophysicist, oceanographer, biomedical engineer, communications engineer, economist, statistician, physicist, etc.

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Über die Autorin bzw. den Autor

Steven M. Kay is one of the world’s leading experts in statistical signal processing. Currently Professor of Electrical Engineering at the University of Rhode Island, Kingston, he has consulted for numerous industrial concerns, the Air Force, Army, and Navy, and has taught short courses to scientists and engineers at NASA and the CIA. Dr. Kay is a Fellow of the IEEE, and a member of Tau Beta Pi, and Sigma Xi and Phi Kappa Phi. He has received the Education Award for “outstanding contributions in education and in writing scholarly book and texts…” from the IEEE Signal Processing society and has been listed as among the 250 most cited researchers in the world in engineering.

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For those involved in the design and implementation of signal processing algorithms, this book strikes a balance between highly theoretical expositions and the more practical treatments, covering only those approaches necessary for obtaining an optimal estimator and analyzing its performance. Author Steven M. Kay discusses classical estimation followed by Bayesian estimation, and illustrates the theory with numerous pedagogical and real-world examples. Special features include over 230 problems designed to reinforce basic concepts and to derive additional results; summary chapter containing an overview of all principal methods and the rationale for choosing a particular one; unified treatment of Wiener and Kalman filtering; estimation approaches for complex data and parameters; and over 100 examples, including real-world applications to high resolution spectral analysis, system identification, digital filter design, adaptive noise cancelation, adaptive beamforming, tracking and localization, and more. Students as well as practicing engineers will find Fundamentals of Statistical Signal Processing an invaluable introduction to parameter estimation theory and a convenient reference for the design of successful parameter estimation algorithms.

Details zur Ausgabe

• Verlag: Pearson
• Erscheinungsdatum: 1993
• Sprache: Englisch
• ISBN 10: 0133457117
• ISBN 13: 9780133457117
• Einband: Gebundene Ausgabe
• Auflage: 1
• Anzahl der Seiten: 608
• Kontakt zum Hersteller: Pearson Benelux BV; productsafety@pearson.com; ; Kabelweg 37; Amsterdam; 1014 BA; Niederlande