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首页> 外文期刊>The journal of fourier analysis and applications >Near-Optimal Encoding for Sigma-Delta Quantization of Finite Frame Expansions
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Near-Optimal Encoding for Sigma-Delta Quantization of Finite Frame Expansions

机译:有限帧扩展的Sigma-Delta量化的近最佳编码

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摘要

In this paper we investigate encoding the bit-stream resulting from coarse Sigma-Delta quantization of finite frame expansions (i.e., overdetermined representations) of vectors. We show that for a wide range of finite-frames, including random frames and piecewise smooth frames, there exists a simple encoding algorithm-acting only on the Sigma-Delta bit stream-and an associated decoding algorithm that together yield an approximation error which decays exponentially in the number of bits used. The encoding strategy consists of applying a discrete random operator to the Sigma-Delta bit stream and assigning a binary codeword to the result. The reconstruction procedure is essentially linear and equivalent to solving a least squares minimization problem.
机译:在本文中,我们研究了对矢量的有限帧扩展(即超定表示)的粗Sigma-Delta量化所产生的比特流的编码。我们表明,对于包括随机帧和分段平滑帧在内的各种有限帧,都存在一种简单的编码算法(仅作用于Sigma-Delta比特流)以及相关联的解码算法,这些算法共同产生了近似误差,该误差会衰减使用的位数呈指数增长。编码策略包括将离散随机算符应用于Sigma-Delta比特流,并为结果分配二进制码字。重建过程本质上是线性的,并且等效于解决最小二乘最小化问题。

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