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Finite-Length Bounds for Joint Source-Channel Coding with Markovian Source and Additive Channel Noise to Achieve Large and Moderate Deviation Bounds

Published 12 Jan 2017 in cs.IT and math.IT | (1701.03305v2)

Abstract: We derive novel upper and lower finite-length bounds of the error probability in joint source-channel coding when the source obeys an ergodic Markov process and the channel is a Markovian additive channel or a Markovian conditional additive channel. These bounds are tight in the large and moderate deviation regimes.

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Authors (2)

  1. Ryo Yaguchi 
  2. Masahito Hayashi 

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