Extensions of jump Markov system estimation techniques

In this paper, we review the framework for fault modeling and identification using jump Markov systems. We derive a special case of an estimation problem where the Viterbi algorithm holds, allowing the most-likely model path to be computed recursively in time, with fixed computational requirements at each time step. In the same case, the model probability at each time step can also be calculated exactly, with fixed computation. We also present a new heuristic, and evaluate it´s performance on a well-known example.