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Lectures on Discrete Time Filtering (Paperback, Softcover reprint of the original 1st ed. 1994)
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Lectures on Discrete Time Filtering (Paperback, Softcover reprint of the original 1st ed. 1994)
Series: Signal Processing and Digital Filtering
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The theory of linear discrete time filtering started with a paper
by Kol mogorov in 1941. He addressed the problem for stationary
random se quences and introduced the idea of the innovations
process, which is a useful tool for the more general problems
considered here. The reader may object and note that Gauss
discovered least squares much earlier; however, I want to
distinguish between the problem of parameter estimation, the Gauss
problem, and that of Kolmogorov estimation of a process. This sep
aration is of more than academic interest as the least squares
problem leads to the normal equations, which are numerically ill
conditioned, while the process estimation problem in the linear
case with appropriate assumptions leads to uniformly asymptotically
stable equations for the estimator and the gain. The conditions
relate to controlability and observability and will be detailed in
this volume. In the present volume, we present a series of lectures
on linear and nonlinear sequential filtering theory. The theory is
due to Kalman for the linear colored observation noise problem; in
the case of white observation noise it is the analog of the
continuous-time Kalman-Bucy theory. The discrete time filtering
theory requires only modest mathematical tools in counterpoint to
the continuous time theory and is aimed at a senior-level
undergraduate course. The present book, organized by lectures, is
actually based on a course that meets once a week for three hours,
with each meeting constituting a lecture."
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