Nonlinear Filtering and Optimal Phase Tracking

Zeev Schuss

ISBN 10: 1489973818 / ISBN 13: 9781489973818

Published by Springer, Springer Jan 2014, 2014

About this Item

This item is printed on demand - Print on Demand Titel. Neuware -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 bookis 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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 280 pp. Englisch.

Seller Inventory # 9781489973818

Bibliographic Details

• Title: Nonlinear Filtering and Optimal Phase Tracking
• Publisher: Springer, Springer Jan 2014
• Publication Date: 2014
• Language: English
• ISBN 10: 1489973818
• ISBN 13: 9781489973818
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 235W x 155H x 16D millimeters 235 millimeters width by 155 millimeters height by 16 millimeters depth
• Weight: 429 grams

About this title

Synopsis

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.

About the Author

Zeev Schuss is a Professor in the School of Mathematical Sciences at Tel Aviv University.