Filtering, smoothing and M-ary detection with discrete time Poisson observations
In this article, we solve a class of estimation problems, namely, filtering smoothing and detection for a discrete time dynamical system with integer-valued observations. The observation processes we consider are Poisson random variables observed at discrete times. Here, the distribution parameter for each Poisson observation is determined by the state of a Markov chain. By appealing to a duality between forward (in time) filter and its corresponding backward processes, we compute dynamics...[Show more]
|Collections||ANU Research Publications|
|Source:||Stochastic Processes and their Applications|
|01_Elliott_Filtering,_smoothing_and_M-ary_2005.pdf||161.86 kB||Adobe PDF||Request a copy|
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