scholarly journals Gaussian Source Coding using a Simple Switched Quantization Algorithm and Variable Length Codewords

2020 ◽  
Vol 20 (4) ◽  
pp. 11-18
Author(s):  
Z. PERIC ◽  
G. PETKOVIC ◽  
B. DENIC ◽  
A. STANIMIROVIC ◽  
V. DESPOTOVIC ◽  
...  
Keyword(s):  
Source Coding ◽  
Variable Length ◽  
Gaussian Source

scholarly journals Distributed Recovery of a Gaussian Source in Interference with Successive Lattice Processing

Entropy ◽  
2019 ◽  
Vol 21 (9) ◽  
pp. 845 ◽  
Author(s):  
Christian Chapman ◽  
Matthew Kinsinger ◽  
Ameya Agaskar ◽  
Daniel W. Bliss
Keyword(s):  
Upper Bound ◽  
Mean Squared Error ◽  
Source Coding ◽  
Power Reduction ◽  
Search Problem ◽  
Squared Error ◽  
Reduction Property ◽  
Gaussian Source ◽  
Parameter Search

A scheme for recovery of a signal by distributed listeners in the presence of Gaussian interference is constructed by exhausting an “iterative power reduction” property. An upper bound for the scheme’s achieved mean-squared-error distortion is derived. The strategy exposes a parameter search problem, which, when solved, causes the scheme to outperform others of its kind. Performance of a blocklength-one scheme is simulated and is seen to improve over plain source coding without compression in the presence of many interferers, and experiences less outages over ensembles of channels.

scholarly journals Asymptotic Rate-Distortion Analysis of Symmetric Remote Gaussian Source Coding: Centralized Encoding vs. Distributed Encoding

Entropy ◽  
2019 ◽  
Vol 21 (2) ◽  
pp. 213 ◽  
Author(s):  
Yizhong Wang ◽  
Li Xie ◽  
Siyao Zhou ◽  
Mengzhen Wang ◽  
Jun Chen
Keyword(s):  
Mean Squared Error ◽  
Source Coding ◽  
Rate Distortion ◽  
Asymptotic Rate ◽  
Squared Error ◽  
Simple Characterization ◽  
Distortion Functions ◽  
Distortion Analysis ◽  
Gaussian Source ◽  
Multivariate Gaussian

Consider a symmetric multivariate Gaussian source with ℓ components, which are corrupted by independent and identically distributed Gaussian noises; these noisy components are compressed at a certain rate, and the compressed version is leveraged to reconstruct the source subject to a mean squared error distortion constraint. The rate-distortion analysis is performed for two scenarios: centralized encoding (where the noisy source components are jointly compressed) and distributed encoding (where the noisy source components are separately compressed). It is shown, among other things, that the gap between the rate-distortion functions associated with these two scenarios admits a simple characterization in the large ℓ limit.

scholarly journals Minimum Expected Distortion in Gaussian Source Coding With Fading Side Information

2012 ◽  
Vol 58 (9) ◽  
pp. 5725-5739 ◽  
Author(s):  
Chris T. K. Ng ◽  
Chao Tian ◽  
Andrea J. Goldsmith ◽  
Shlomo Shamai
Keyword(s):  
Source Coding ◽  
Side Information ◽  
Gaussian Source

Practical considerations for variable length source coding

2005 ◽  
Author(s):  
D. Cohn ◽  
J. Melsa ◽  
A. Arora ◽  
J. Kresse ◽  
A. Pande
Keyword(s):  
Source Coding ◽  
Variable Length

scholarly journals Gaussian source coding with spherical codes

2002 ◽  
Vol 48 (11) ◽  
pp. 2980-2989 ◽  
Author(s):  
J. Hamkins ◽  
K. Zeger
Keyword(s):  
Source Coding ◽  
Spherical Codes ◽  
Gaussian Source

Weak variable-length source coding

2000 ◽  
Vol 46 (4) ◽  
pp. 1217-1226 ◽  
Author(s):  
Te Sun Han
Keyword(s):  
Source Coding ◽  
Variable Length
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