无记忆采样率失真

Vinay Praneeth Boda, P. Narayan
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引用次数: 2

摘要

考虑一个具有m个分量源的离散无内存多源。在每个时刻采样k≤m个源的子集并进行联合压缩,以便在给定的失真准则下重构所有m个源。采样率失真函数的特征是用于无记忆随机采样的情况,采样器可能依赖于源输出;解码器被告知采样集的序列。通过对最优采样器结构的检验,表明以条件点质量为特征的确定性采样就足够了。还讨论了抽样的限制形式。当解码器不被告知采样集的序列时,提供采样率失真函数的上界。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Memoryless sampling rate distortion
Consider a discrete memoryless multiple source with m component sources. A subset of k ≤ m sources are sampled at each time instant and jointly compressed in order to reconstruct all the m sources under a given distortion criterion. A sampling rate distortion function is characterized for the case of memoryless random sampling with the sampler possibly depending on the source outputs; and the decoder is informed of the sequence of sampled sets. Examining the structure of the optimal sampler, it is shown that deterministic sampling, characterized by a conditional point-mass, suffices. Restricted forms of sampling are also addressed. An upper bound for the sampling rate distortion function is provided when the decoder is not informed of the sequence of sampled sets.
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