scholarly journals Fixed-Rate Zero-Delay Source Coding for Stationary Vector-Valued Gauss-Markov Sources

2018 ◽  
Author(s):  
Photios A. Stavrou ◽  
Jan Ostergaard
Keyword(s):  
Source Coding ◽  
Fixed Rate ◽  
Vector Valued ◽  
Stationary Vector ◽  
Markov Sources

Fixed-rate universal codes for Markov sources

1978 ◽  
Vol 24 (3) ◽  
pp. 360-367 ◽  
Author(s):  
D. Neuhoff ◽  
P. Shields
Keyword(s):  
Fixed Rate ◽  
Universal Codes ◽  
Markov Sources

scholarly journals Fixed-Rate Universal Lossy Source Coding and Model Identification: Connection with Zero-Rate Density Estimation and the Skeleton Estimator

Entropy ◽  
2018 ◽  
Vol 20 (9) ◽  
pp. 640 ◽  
Author(s):  
Jorge Silva ◽  
Milan Derpich
Keyword(s):  
Density Estimation ◽  
Source Coding ◽  
Model Identification ◽  
Fixed Rate ◽  
Original Result ◽  
Totally Bounded ◽  
Learning Framework ◽  
Zero Rate ◽  
The Rich ◽  
Necessary And Sufficient

This work demonstrates a formal connection between density estimation with a data-rate constraint and the joint objective of fixed-rate universal lossy source coding and model identification introduced by Raginsky in 2008 (IEEE TIT, 2008, 54, 3059–3077). Using an equivalent learning formulation, we derive a necessary and sufficient condition over the class of densities for the achievability of the joint objective. The learning framework used here is the skeleton estimator, a rate-constrained learning scheme that offers achievable results for the joint coding and modeling problem by optimally adapting its learning parameters to the specific conditions of the problem. The results obtained with the skeleton estimator significantly extend the context where universal lossy source coding and model identification can be achieved, allowing for applications that move from the known case of parametric collection of densities with some smoothness and learnability conditions to the rich family of non-parametric L 1 -totally bounded densities. In addition, in the parametric case we are able to remove one of the assumptions that constrain the applicability of the original result obtaining similar performances in terms of the distortion redundancy and per-letter rate overhead.

scholarly journals Distributed Joint Source Coding and Trellis Coded Modulation for Symbol-Based Markov Sources

2018 ◽  
Vol 67 (5) ◽  
pp. 4031-4041
Author(s):  
Mohd Azri Mohd Izhar ◽  
Abdulah Jeza Aljohani ◽  
Soon Xin Ng ◽  
Lajos Hanzo
Keyword(s):  
Source Coding ◽  
Coded Modulation ◽  
Trellis Coded Modulation ◽  
Trellis Coded ◽  
Markov Sources
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