Information content in Gaussian noise: optimal compression rates
摘要
We approach the theoretical problem of compressing a signal dominated by Gaussian noise. We present expressions for the compression ratio which can be reached, under the light of Shannon's noiseless coding theorem, for a linearly quantized stochastic Gaussian signal (noise). The compression ratio decreases logarithmically with the amplitude of the frequency spectrum of the noise. Entropy values and compression rates are shown to depend on the shape of this power spectrum, given different normalizations. The cases of white noise (w.n.), power-law noise ---including noise---, (w.n.) noise, and piecewise (w.n.+ w.n.) noise are discussed, while quantitative behaviours and useful approximations are provided.
引用
@article{arxiv.physics/9809004,
title = {Information content in Gaussian noise: optimal compression rates},
author = {August Romeo and Enrique Gaztanaga and Jose Barriga and Emilio Elizalde},
journal= {arXiv preprint arXiv:physics/9809004},
year = {2009}
}
备注
28 LateX pages and 6 Fig, replaced with minor changes to match published version