Large Deviation Techniques in Decision, Simulation and Estimation
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Large Deviation Techniques in Decision, Simulation and Estimation: (Probability & Mathematical Statistics S.)

Large Deviation Techniques in Decision, Simulation and Estimation: (Probability & Mathematical Statistics S.)


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About the Book

Random Data Analysis and Measurement Procedures Second Edition Julius S. Bendat and Allan G. Piersol The latest techniques for analysis and measurement of stationary and nonstationary random data passing through physical systems are described in this extensive revision and update. It includes new modern data processing procedures and new statistical error analysis formulas for the evaluation of estimates in single input/output and multiple input/output problems, plus new material on Hilbert transforms, multiple array models, and more. Chapters on statistical errors in basic and advanced estimates represent the most complete derivation and summary of these matters in print. 1986 (0 471-04000-2) 566 pp. Linear Stochastic Systems Peter E. Caines This outstanding text provides a unified and mathematically rigorous exposition of linear stochastic system theory The comprehensive format includes a full treatment of the fundamentals of stochastic processes and the construction of stochastic systems. It then presents an integrated view of the interrelated theories of prediction, realization (or modeling), parameter estimation and control. It also features in-depth coverage of system identification, with chapters on maximum likelihood estimation for Gaussian ARMAX and state space systems, minimum prediction error identification methods, nonstationary system identification, linear-quadratic stochastic control and concludes with a discussion of stochastic adaptive control. 1988 (0 471-08101-9) 874 pp. Introduction to the theory of Coverage Processes Peter Hall Coverage processes are finding increasing application in such diverse areas as queueing theory, ballistics, and physical chemistry. Drawing on methodology from several areas of probability theory and mathematics, this monograph provides a succinct and rigorous development of the mathematical theory of models for random coverage patterns. 1988 (0 471-85702-5) 408 pp.

Table of Contents:
Cramir's Theorem and Extensions; Sanov's Theorem and the Contraction Principle; Gaussian Processes and Wentzell-Freidlin Theory; Large Deviations for Markov Processes; Applications to Detection Theory; Asymptotic Expansions; Quick Simulation; Applications to Parameter Estimation; Applications to Information Theory; Appendices; Solutions to Exercises; References; Index.

About the Author :
JAMES A. BUCKLEW is a professor in the Department of Electrical and Computer Engineering at the University of Wisconsin-Madison. He received his PhD in electrical engineering from Purdue in 1979. In 1984 Dr. Bucklew received a Presidential Young Investigator Award. He is currently an associate editor of the IEEE Transactions on Information Theory.


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Product Details
  • ISBN-13: 9780471618560
  • Publisher: John Wiley and Sons Ltd
  • Publisher Imprint: John Wiley & Sons Inc
  • Height: 62 mm
  • Returnable: N
  • Weight: 595 gr
  • ISBN-10: 047161856X
  • Publisher Date: 15 Aug 1990
  • Binding: Hardback
  • Language: English
  • Series Title: Probability & Mathematical Statistics S.
  • Width: 42 mm


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Large Deviation Techniques in Decision, Simulation and Estimation: (Probability & Mathematical Statistics S.)
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