Brief paper: Detection and estimation for abruptly changing systems

Authors:
Jitendra K. Tugnait
Affiliations:
Department of Electrical and Computer Engineering, University of Iowa, Iowa City, IA 52242, U.S.A.
Venue:
Automatica (Journal of IFAC)
Year:
1982

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Abstract

The problem of state estimation and system structure detection for discrete stochastic dynamical systems with parameters which may switch among a finite set of values is considered. The switchings are modelled by a Markov chain with known transition probabilities. A brief survey and a unified treatment of the existing suboptimal algorithms are provided. The optimal algorithms require exponentially increasing memory and computations with time. Simulation results comparing the various suboptimal algorithms are presented.