Asymptotically optimal low-complexity sequential lossless coding for piecewise-stationary memoryless sources .I. The regular case

2000 ◽  
Vol 46 (7) ◽  
pp. 2444-2467 ◽  
Author(s):  
D.J. Costello ◽  
G.I. Shamir
Keyword(s):  
Low Complexity ◽  
Regular Case ◽  
Asymptotically Optimal ◽  
Lossless Coding

scholarly journals A Low-Complexity and Asymptotically Optimal Coding Strategy for Gaussian Vector Sources

Entropy ◽  
2019 ◽  
Vol 21 (10) ◽  
pp. 965
Author(s):  
Marta Zárraga-Rodríguez ◽  
Jesús Gutiérrez-Gutiérrez ◽  
Xabier Insausti
Keyword(s):  
Finite Length ◽  
Correlation Matrix ◽  
Moving Average ◽  
Low Complexity ◽  
Wide Sense ◽  
Gaussian Vector ◽  
Asymptotically Optimal ◽  
Optimal Coding ◽  
Length Data ◽  
Coding Strategy

In this paper, we present a low-complexity coding strategy to encode (compress) finite-length data blocks of Gaussian vector sources. We show that for large enough data blocks of a Gaussian asymptotically wide sense stationary (AWSS) vector source, the rate of the coding strategy tends to the lowest possible rate. Besides being a low-complexity strategy it does not require the knowledge of the correlation matrix of such data blocks. We also show that this coding strategy is appropriate to encode the most relevant Gaussian vector sources, namely, wide sense stationary (WSS), moving average (MA), autoregressive (AR), and ARMA vector sources.

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