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

Louis Shue, S. Dey, Brian Anderson, F. De Bruyne

Research output: Contribution to journalArticlepeer-review

17 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)202-208
JournalIEEE Transactions on Signal Processing
Volume49
Issue number1
DOIs
Publication statusPublished - Jan 2001

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