Performance improvement with decoder output smoothing in differential predictive coding

Abstract

We provide a theoretical analysis of the performance of differential predictive coding using fixed-lag smoothing of the standard decoder output. This performance is compared to related results for coding using latency at the encoder, and causal encoding with delayed decoding, as well as with some prior theoretical analyses of these methods. Surprisingly, it is shown that fixed-lag smoothing of the standard decoder output with causal encoding achieves the asymptotic and finite lag performance promised by a completely reoptimized decoder.