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Trade-off between dimensionality reduction and quantization in minimum mean square error estimation

机译:在最小均方误差估计中的维度降低和量化之间的权衡

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摘要

In this paper, the trade-off between dimension reduction and quantization in minimum mean square error estimation problem is investigated. With given communication bandwidth, the bits allocation problem is formulated as an optimization problem. For high dimension observation case, the optimal allocation strategy is proposed that compresses the observation to a lower dimension, then allocate the given bits to these compressed dimension. Do not waste the bandwidth on the less important dimension which would leads to bad performance.
机译:在本文中,研究了最小均方误差估计问题的尺寸减小和量化之间的折衷。通过给定通信带宽,将BITS分配问题标准为优化问题。对于高尺寸观察案例,提出了最佳分配策略,使得将观察压缩到较低尺寸,然后将给定比特分配给这些压缩尺寸。不要在不太重要的维度上浪费带宽,这会导致性能不佳。

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