๐”– Scriptorium
โœฆ   LIBER   โœฆ

๐Ÿ“

Stochastic Processes and Filtering Theory

โœ Scribed by Andrew H. Jazwinski (Eds.)


Publisher
AP
Year
1970
Tongue
English
Leaves
389
Series
Mathematics in Science and Engineering 64
Category
Library

โฌ‡  Acquire This Volume

No coin nor oath required. For personal study only.

โœฆ Synopsis


This book presents a unified treatment of linear and nonlinear filtering theory for engineers, with sufficient emphasis on applications to enable the reader to use the theory. The need for this book is twofold. First, although linear estimation theory is relatively well known, it is largely scattered in the journal literature and has not been collected in a single source. Second, available literature on the continuous nonlinear theory is quite esoteric and controversial, and thus inaccessible to engineers uninitiated in measure theory and stochastic differential equations. Furthermore, it is not clear from the available literature whether the nonlinear theory can be applied to practical engineering problems. In attempting to fill the stated needs, the author has retained as much mathematical rigor as he felt was consistent with the prime objective-to explain the theory to engineers. Thus, the author has avoided measure theory in this book by using mean square convergence, on the premise that everyone knows how to average. As a result, the author only requires of the reader background in advanced calculus, theory of ordinary differential equations, and matrix analysis.

โœฆ Table of Contents


Content:
Edited by
Page iii

Copyright Page
Page iv

Dedication
Page v

Preface
Pages vii-viii
Andrew H. Jazwinski

Acknowledgments
Page ix

1 Introduction
Pages 1-7

2 Probability Theory and Random Variables
Pages 8-46

3 Stochastic Processes
Pages 47-92

4 Stochastic Differential Equations
Pages 93-141

5 Introduction to Filtering Theory
Pages 142-161

6 Nonlinear Filtering Theory
Pages 162-193

7 Linear Filtering Theory
Pages 194-265

8 Applications of Linear Theory
Pages 266-331

9 Approximate Nonlinear Filters
Pages 332-366

Author Index
Pages 367-370

Subject Index
Pages 371-376


๐Ÿ“œ SIMILAR VOLUMES


Stochastic Processes and Filtering Theor
โœ Andrew H. Jazwinski (Eds.) ๐Ÿ“‚ Library ๐Ÿ“… 1970 ๐Ÿ› Academic Press ๐ŸŒ English

This book presents a unified treatment of linear and nonlinear filtering theory for engineers, with sufficient emphasis on applications to enable the reader to use the theory. The need for this book is twofold. First, although linear estimation theory is relatively well known, it is largely scattere

Stochastic Filtering Theory
โœ Gopinath Kallianpur (auth.) ๐Ÿ“‚ Library ๐Ÿ“… 1980 ๐Ÿ› Springer-Verlag New York ๐ŸŒ English

<p>This book is based on a seminar given at the University of California at Los Angeles in the Spring of 1975. The choice of topics reflects my interests at the time and the needs of the students taking the course. Initially the lectures were written up for publication in the Lecture Notes series. H

Stochastic Filtering Theory
โœ Gopinath Kallianpur (auth.) ๐Ÿ“‚ Library ๐Ÿ“… 1980 ๐Ÿ› Springer-Verlag New York ๐ŸŒ English

<p>This book is based on a seminar given at the University of California at Los Angeles in the Spring of 1975. The choice of topics reflects my interests at the time and the needs of the students taking the course. Initially the lectures were written up for publication in the Lecture Notes series. H

Discrete Stochastic Processes and Optima
โœ Jean-Claude Bertein, Roger Ceschi ๐Ÿ“‚ Library ๐Ÿ“… 2007 ๐Ÿ› ISTE USA ๐ŸŒ English

Optimal filtering applied to stationary and non-stationary signals provides the most efficient means of dealing with problems arising from the extraction of noise signals. Moreover, it is a fundamental feature in a range of applications, such as in navigation in aerospace and aeronautics, filter pro

Discrete Stochastic Processes and Optima
โœ Jean-Claude Bertein, Roger Ceschi ๐Ÿ“‚ Library ๐Ÿ“… 2007 ๐Ÿ› Wiley-ISTE ๐ŸŒ English

Optimal filtering applied to stationary and non-stationary signals provides the most efficient means of dealing with problems arising from the extraction of noise signals. Moreover, it is a fundamental feature in a range of applications, such as in navigation in aerospace and aeronautics, filter pro