Linear and nonlinear filtering for scientists and engineers
Author(s)
Bibliographic Information
Linear and nonlinear filtering for scientists and engineers
World Scientific, c1998
- Other Title
-
Perspectives in hadronic physics, proceedings of the Conference
Available at 6 libraries
  Aomori
  Iwate
  Miyagi
  Akita
  Yamagata
  Fukushima
  Ibaraki
  Tochigi
  Gunma
  Saitama
  Chiba
  Tokyo
  Kanagawa
  Niigata
  Toyama
  Ishikawa
  Fukui
  Yamanashi
  Nagano
  Gifu
  Shizuoka
  Aichi
  Mie
  Shiga
  Kyoto
  Osaka
  Hyogo
  Nara
  Wakayama
  Tottori
  Shimane
  Okayama
  Hiroshima
  Yamaguchi
  Tokushima
  Kagawa
  Ehime
  Kochi
  Fukuoka
  Saga
  Nagasaki
  Kumamoto
  Oita
  Miyazaki
  Kagoshima
  Okinawa
  Korea
  China
  Thailand
  United Kingdom
  Germany
  Switzerland
  France
  Belgium
  Netherlands
  Sweden
  Norway
  United States of America
Note
Bibliography: p. 247-253
Includes index
Description and Table of Contents
Description
The book combines both rigor and intuition to derive most of the classical results of linear and nonlinear filtering and beyond. Many fundamental results recently discovered by the author are included. Furthermore, many results that have appeared in recent years in the literature are also presented. The most interesting feature of the book is that all the derivations of the linear filter equations given in Chapters 3-11, beginning from the classical Kalman filter presented in Chapters 3 and 5, are based on one basic principle which is fully rigorous but also very intuitive and easily understandable. The second most interesting feature is that the book provides a rigorous theoretical basis for the numerical solution of nonlinear filter equations illustrated by multidimensional examples. The book also provides a strong foundation for theoretical understanding of the subject based on the theory of stochastic differential equations.
Table of Contents
- Introduction to stochastic processes
- stochastic differential equations
- Kalman filtering for linear systems driven by Weiner process I
- Kalman filtering for linear systems driven by Weiner process II
- discrete Kalman filtering
- linear filtering with correlated noise I
- linear filtering with correlated noise II
- linear filtering with correlated noise III
- linear filtering of jump processes
- linear filtering with constraints
- filtering for linear systems driven by second order random processes
- extended Kalman filtering I,II, and III
- nonlinear filtering
- numerical techniques for nonlinear filtering
- partially observed control
- system identification.
by "Nielsen BookData"