Wang Yizhong, Xie Li, Zhou Siyao, Wang Mengzhen, Chen Jun
College of Electronic Information and Automation, Tianjin University of Science and Technology, Tianjin 300222, China.
Department of Electrical System of Launch Vehicle, Institute of Aerospace System Engineering Shanghai, Shanghai Academy of Spaceflight Technology, Shanghai 201109, China.
Entropy (Basel). 2019 Feb 23;21(2):213. doi: 10.3390/e21020213.
Consider a symmetric multivariate Gaussian source with 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 limit.
考虑一个具有(n)个分量的对称多元高斯源，这些分量被独立同分布的高斯噪声所干扰；这些有噪声的分量以一定速率进行压缩，并且利用压缩后的版本在均方误差失真约束下重建源。针对两种情况进行了率失真分析：集中式编码（其中有噪声的源分量被联合压缩）和分布式编码（其中有噪声的源分量被分别压缩）。除其他事项外，结果表明，在大(n)极限情况下，与这两种情况相关的率失真函数之间的差距具有简单的特征描述。
