Title :
Nonlinear filtering with counting observations
Author :
Segall, Adrian ; Davis, Mark H A ; Kailath, Thomas
fDate :
3/1/1975 12:00:00 AM
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;
Journal_Title :
Information Theory, IEEE Transactions on
DOI :
10.1109/TIT.1975.1055360
