DocumentCode :
3022968
Title :
Nonstatistical nonlinear filtering
Author :
Mortensen, R.E.
Author_Institution :
University of California, Los Angeles, CA
fYear :
1979
fDate :
10-12 Jan. 1979
Firstpage :
130
Lastpage :
132
Abstract :
Modern statistical continuous-time nonlinear filtering theory has become so esoteric that its utility for practical applications is frequently questioned. This paper examines whether there may be an alternative rationale for arriving at a plausible nonlinear filter which could be more readily implemented in practice. This rationale dispenses with statistics entirely and approaches the problem as nonlinear least squares curve fitting. In order to do this we consider only a model which contains observation "noise" only, and no state "noise". The object is not so much to come up with a specific filter which solves a specific problem as to gain insight into the nature of the obstacles to computational ease which seem inherent in any formulation.
Keywords :
Calculus; Equations; Filtering; Filters;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Decision and Control including the 17th Symposium on Adaptive Processes, 1978 IEEE Conference on
Conference_Location :
San Diego, CA, USA
Type :
conf
DOI :
10.1109/CDC.1978.267906
Filename :
4046093
Link To Document :
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