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首页> 外文期刊>IEEE Transactions on Signal Processing >Asymptotic Design of Quantizers for Decentralized MMSE Estimation
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Asymptotic Design of Quantizers for Decentralized MMSE Estimation

机译:分散MMSE估计量化器的渐近设计。

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摘要

Conceptual and practical encoding/decoding, aimed at accurately reproducing remotely collected observations, has been heavily investigated since the pioneering works by Shannon about source coding. However, when the goal is not to reproduce the observables, but making inference about an embedded parameter and the scenario consists of many unconnected remote nodes, the landscape is less certain. We consider a multiterminal system designed for efficiently estimating a random parameter according to the minimum mean square error (MMSE) criterion. The analysis is limited to scalar quantizers followed by a joint entropy encoder, and it is performed in the high-resolution regime where the problem can be more easily mathematically tackled. Focus is made on the peculiarities deriving from the estimation task, as opposed to that of reconstruction, as well as on the multiterminal, as opposite to centralized, character of the inference. The general form of the optimal nonuniform quantizer is derived and examples are given.
机译:自香农(Shannon)在源代码编码方面的开创性工作以来,旨在准确再现远程收集到的观测结果的概念性和实用性的编码/解码已得到大量研究。但是,当目标不是重现可观察对象,而是推断嵌入式参数并且场景由许多未连接的远程节点组成时,情况就不太确定了。我们考虑了一种多终端系统,该系统旨在根据最小均方误差(MMSE)准则有效地估计随机参数。该分析仅限于标量量化器,后跟联合熵编码器,并且该分析是在高分辨率方案中执行的,在高分辨率方案中可以更轻松地数学解决该问题。着重于与重建相反的,来自估计任务的特性,以及与推理的集中特性相反的多终端特性。推导了最佳非均匀量化器的一般形式,并给出了例子。

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