DocumentCode
923101
Title
Nonlinear filtering with counting observations
Author
Segall, Adrian ; Davis, Mark H A ; Kailath, Thomas
Volume
21
Issue
2
fYear
1975
fDate
3/1/1975 12:00:00 AM
Firstpage
143
Lastpage
149
Abstract
We apply some recent results in martingale theory and the innovations method to obtain the evolution of the conditional mean and conditional density of a process that modulates the rate of a counting process.
Keywords
Innovations methods (stochastic processes); Jump processes; Least-squares estimation; Martingales; Nonlinear filtering; AWGN; Additive white noise; Filtering; Gaussian noise; Mathematics; Nonlinear filters; Signal processing; Statistics; Stochastic processes; Technological innovation;
fLanguage
English
Journal_Title
Information Theory, IEEE Transactions on
Publisher
ieee
ISSN
0018-9448
Type
jour
DOI
10.1109/TIT.1975.1055360
Filename
1055360
Link To Document