Overview
- Many exercises and examples included
- Balance between mathematical rigor and physical intuition
- An analytical rather than measure-theoretical approach to the derivation and solution of the partial differential equations of nonlinear filltering theory
Part of the book series: Applied Mathematical Sciences (AMS, volume 180)
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Table of contents (7 chapters)
Keywords
About this book
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This book offers an analytical rather than measure-theoretical approach to the derivation of the partial differential equations of nonlinear filtering theory. The basis for this approach is the discrete numerical scheme used in Monte-Carlo simulations of stochastic differential equations and Wiener's associated path integral representation of the transition probability density. Furthermore, it presents analytical methods for constructing asymptotic approximations to their solution and for synthesizing asymptotically optimal filters. It also offers a new approach to the phase tracking problem, based on optimizing the mean time to loss of lock. The book is based on lecture notes from a one-semester special topics course on stochastic processes and their applications that the author taught many times to graduate students of mathematics, applied mathematics, physics, chemistry, computer science, electrical engineering, and other disciplines. The book contains exercises and worked-out examples aimed at illustrating the methods of mathematical modeling and performance analysis of phase trackers.Authors and Affiliations
About the author
Bibliographic Information
Book Title: Nonlinear Filtering and Optimal Phase Tracking
Authors: Zeev Schuss
Series Title: Applied Mathematical Sciences
DOI: https://doi.org/10.1007/978-1-4614-0487-3
Publisher: Springer New York, NY
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer Science+Business Media, LLC 2012
Hardcover ISBN: 978-1-4614-0486-6Published: 15 November 2011
Softcover ISBN: 978-1-4899-7381-8Published: 25 January 2014
eBook ISBN: 978-1-4614-0487-3Published: 16 November 2011
Series ISSN: 0066-5452
Series E-ISSN: 2196-968X
Edition Number: 1
Number of Pages: XVIII, 262
Topics: Probability Theory and Stochastic Processes, Theoretical, Mathematical and Computational Physics, Partial Differential Equations