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A comparison between optimal and Kalman filtering for hidden Markov processes

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1 Author(s)
L. B. White ; Div. of Commun., Defence Sci. & Technol. Organ., Salisbury, SA, Australia

This paper gives sufficient conditions for specifying the optimal linear filters for a hidden Markov process (HMP) and compares its performance with the optimal (i.e., minimum conditional variance) filter derived from the corresponding hidden Markov model using a simulation. The optimal filter performs much better at high signal-to-noise ratio (SNR) but the performance loss using the linear filter reduces as the SNR decreases.

Published in:

IEEE Signal Processing Letters  (Volume:5 ,  Issue: 5 )