A novel correlation model for universal compression of parametric sources

Ahmad Beirami, F. Fekri
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引用次数: 1

Abstract

In this paper, we consider k parametric sources with unknown source parameter vectors. In this setup, we propose a novel correlation model where the degree of correlation of each parameter vector is governed by a single variable. We derive the properties of the parameter vectors. In particular, we derive bounds on the correlation between the parameter vectors and show show that this will include independence all the way to convergence in mean square sense. Then, we set up the minimax and maximin games in universal compression and characterize the compression risk under the proposed correlation model when side information from one other source is available at both the encoder and the decoder.
一种新的参数源通用压缩相关模型
本文考虑具有未知源参数向量的k个参数源。在这种设置中,我们提出了一种新的相关模型,其中每个参数向量的相关程度由单个变量控制。我们推导出参数向量的性质。特别地,我们推导了参数向量之间的相关界限并证明了这将包括独立性一直到均方意义上的收敛。然后,我们建立了通用压缩的极大极小和极大对策,并描述了在所提出的相关模型下,当编码器和解码器都有另一个源的侧信息时的压缩风险。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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