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On state-estimation of a two-state hidden Markov model with quantization

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4 Author(s)
Shue, L. ; Centre for Signal Process., Nanyang Technol. Inst., Singapore ; Dey, S. ; Anderson, B.D.O. ; De Bruyne, F.

We consider quantization from the perspective of minimizing filtering error when quantized instead of continuous measurements are used as inputs to a nonlinear filter, specializing to discrete-time two-state hidden Markov models (HMMs) with continuous-range output. An explicit expression for the filtering error when continuous measurements are used is presented. We also propose a quantization scheme based on maximizing the mutual information between quantized observations and the hidden states of the HMM

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Signal Processing, IEEE Transactions on  (Volume:49 ,  Issue: 1 )