A Maximum Likelihood Estimationfor Markov-modulated Poisson Processes
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Abstract:
During the last decade,Hidden Markov Models (HMMs) have become a widespread tool for modeling sequence of dependent variables. Parameter estimation of HMMs is most important in actual application. By changing continued-time HMMs into discrete-time HMMs, we consider maximum likelihood estimation for a special HMMs which is called Markov-modulated Poisson processes. Such processes have been proposed for modeling traffic streams in complex telecommunication networks.
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WANG Chunling, LI Bing, GE Zhengkun. A Maximum Likelihood Estimationfor Markov-modulated Poisson Processes[J]. Journal of National University of Defense Technology,2002,24(3):27-31.