Alternating Markov Chains for Distribution Estimation in the Presence of Errors

Details Alternating Markov Chains for Distribution Estimation in the Presence of Errors Alternating Markov Chains for Distribution Estimation in the Presence of Errors

2012-02-04

arxiv.org/abs/1202.0925v1

Computer Science

Information Theory

Scientific paper

We consider a class of small-sample distribution estimators over noisy channels. Our estimators are designed for repetition channels, and rely on properties of the runs of the observed sequences. These runs are modeled via a special type of Markov chains, termed alternating Markov chains. We show that alternating chains have redundancy that scales sub-linearly with the lengths of the sequences, and describe how to use a distribution estimator for alternating chains for the purpose of distribution estimation over repetition channels.

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