Title :
Filters for estimating Markov modulated Poisson processes and image-enchanced tracking
Author :
Krishnamurthy, Vikram ; Elliot, R.J.
Author_Institution :
Dept. of Electr. & Electron. Eng., Melbourne Univ., Parkville, Vic., Australia
Abstract :
We present algorithms for state and parameter estimation of Markov modulated Poisson processes (MMPP). We first derive finite dimensional innovations and Zakai filters for various statistics of a MMPP. Using these filters, a filter-based expectation-maximization algorithm is derived for computing maximum-likelihood parameter estimates. Finally we present an application of the techniques in image enchanced tracking
Keywords :
Markov processes; filtering theory; identification; image enhancement; statistical analysis; stochastic processes; tracking; Markov modulated Poisson processes; Zakai filters; filter-based expectation-maximization algorithm; finite-dimensional innovations; image-enchanced tracking; maximum-likelihood parameter estimates; state estimation; Linear systems; Noise generators; Optical fiber networks; Optical filters; Optical modulation; Optical packet switching; Parameter estimation; Statistics; Target tracking; Technological innovation;
Conference_Titel :
Decision and Control, 1995., Proceedings of the 34th IEEE Conference on
Conference_Location :
New Orleans, LA
Print_ISBN :
0-7803-2685-7
DOI :
10.1109/CDC.1995.478569
