A Framework for Mixed Estimation of Hidden Markov Models

Abstract

In this paper, we present a framework for a mixed estimationscheme for hidden Markov models (HMM).A robust estimation scheme is first presented using the minimax method thatminimizes a worst case cost for HMMs with bounded uncertainties.Then we present a mixed estimation scheme that minimizes arisk-neutral cost with a constraint on the worst-case cost. Somesimulation results are also presented to compare these different estimationschemes in cases of uncertainties in the noise model.The research and scientific content in this material has been accepted for presentation in the 37th IEEE Conference on Decision and Control, Tampa, December 1998.