Framework for Mixed Estimation of Hidden Markov Models

摘要

In this paper, we present a framework for a mixed estimation scheme for hidden Markov models (HMM). A robust estimation scheme is first presented using the minimax method that minimizes a worst case cost for HMMs with bounded uncertainties. Then we present a mixed estimation scheme that minimizes a risk- neutral cost with a constraint on the worst-case cost. Some simulation results are also presented to compare these different estimation schemes in cases of uncertainties in the noise model.