Stochastic Processes and Filtering Theory

Stochastic Processes and Filtering Theory

by Andrew H. Jazwinski


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Stochastic Processes and Filtering Theory by Andrew H. Jazwinski

This unified treatment of linear and nonlinear filtering theory presents material previously available only in journals, and in terms accessible to engineering students. Its sole prerequisites are advanced calculus, the theory of ordinary differential equations, and matrix analysis. Although theory is emphasized, the text discusses numerous practical applications as well.
Taking the state-space approach to filtering, this text models dynamical systems by finite-dimensional Markov processes, outputs of stochastic difference, and differential equations. Starting with background material on probability theory and stochastic processes, the author introduces and defines the problems of filtering, prediction, and smoothing. He presents the mathematical solutions to nonlinear filtering problems, and he specializes the nonlinear theory to linear problems. The final chapters deal with applications, addressing the development of approximate nonlinear filters, and presenting a critical analysis of their performance.

Product Details

ISBN-13: 9780486462745
Publisher: Dover Publications
Publication date: 11/12/2007
Series: Dover Books on Electrical Engineering Series
Pages: 402
Sales rank: 825,833
Product dimensions: 5.50(w) x 8.50(h) x 0.82(d)

Table of Contents

1. Introduction
2. Probability Theory and Random Variables
3. Stochastic Processes
4. Stochastic Differential Equations
5. Introduction to Filtering Theory
6. Nonlinear Filtering Theory
7. Linear Filtering Theory
8. Applications of Linear Theory
9. Approximate Nonlinear Filters
Author index
Subject index

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