文章基本信息

标题：Optimal Nonlinear Readout under Strong Non-Gaussian Noise
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作者：Akihisa ICHIKI ; Yukihiro TADOKORO
期刊名称：Interdisciplinary Information Sciences
印刷版ISSN：1340-9050
电子版ISSN：1347-6157
出版年度：2013
卷号：19
期号：1
页码：23-28
DOI：10.4036/iis.2013.23
出版社：The Editorial Committee of the Interdisciplinary Information Sciences
摘要：The optimal nonlinearity for readout a weak signal embedded in strong noise is investigated. In practical devices, a high signal-to-noise ratio (SNR) is preferred more than the Bayesian estimation, which generally requires complicated calculations. The optimal nonlinearity is determined by the noise statistics including its temporal correlations, and provides the highest SNR. According to the result, the existence of nonlinear devices that exhibit SNR higher than linear devices is shown under non-Gaussian noise. In contrast, linear devices exhibit the highest SNR in the presence of Gaussian noise. Using the resultant nonlinearity, the Cramér–Rao lower bound is realized by an easy linear estimator. Our derivation of the optimal characteristics of the filter gives the criterion to designed practical devices in the presence of noise.
关键词：nonlinear filter;non-Gaussian noise;colored noise;signal-to-noise ratio;linear estimator