Source Coding With Feed-Forward: Rate-Distortion Theorems and Error Exponents for a General Source

Authors:
R. Venkataramanan;S. Sandeep Pradhan
Affiliations:
Univ. of Michigan, Ann Arbor;-
Venue:
IEEE Transactions on Information Theory
Year:
2007

Citing 0
Cited 6

Motif discovery in tissue-specific regulatory sequences using directed information

EURASIP Journal on Bioinformatics and Systems Biology
Finite state channels with time-invariant deterministic feedback

IEEE Transactions on Information Theory
Directed information, causal estimation, and communication in continuous time

WiOPT'09 Proceedings of the 7th international conference on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks
On computing the feedback capacity of channels and the feed-forward rate-distortion function of sources

IEEE Transactions on Communications
Estimating the directed information to infer causal relationships in ensemble neural spike train recordings

Journal of Computational Neuroscience
On directed information theory and Granger causality graphs

Journal of Computational Neuroscience

Quantified Score

Hi-index	754.90

Visualization

Abstract

In this work, we consider a source coding model with feed-forward. We analyze a system with a noiseless, feed-forward link where the decoder has knowledge of all previous source samples while reconstructing the present sample. The rate-distortion function for an arbitrary source with feed-forward is derived in terms of directed information, a variant of mutual information. We further investigate the nature of the rate-distortion function with feed-forward for two common types of sources- discrete memory- less sources and Gaussian sources. We then characterize the error exponent for a general source with feed-forward. The results are then extended to feed-forward with an arbitrary delay larger than the block length.