Some more robustness conditions for the invariant density of a class of 1D maps under additive noise

S. Callegari
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引用次数: 3

Abstract

Circuits based on chaotic maps are increasingly appealing to synthesize signals with prescribed statistical features. However, in their implementation one should not forget that electronic noise can affect the statistics, even by a large amount. Although dealing with the effects of noise on a strongly nonlinear system can be hard, it has recently been proved that classes of chaotic maps exist whose invariant density is completely insensitive to it, a property that makes them particularly well suited for implementation. This paper builds upon that initial framework, offering a wider set of sufficient conditions for general noise robustness. It also illustrates that other noise robustness mechanisms exist when the particular (yet reasonable) assumption of symmetrically distributed noise is made.
一类一维映射在加性噪声下密度不变的鲁棒性条件
基于混沌映射的电路在合成具有规定统计特征的信号方面越来越有吸引力。然而,在实施过程中,不应忘记电子噪声会影响统计数据,甚至影响很大。尽管在强非线性系统中处理噪声的影响可能很困难,但最近已经证明存在一类混沌映射,其不变密度对噪声完全不敏感,这一特性使它们特别适合于实现。本文建立在初始框架的基础上,为一般噪声鲁棒性提供了更广泛的充分条件。它还说明,当做出对称分布噪声的特定(但合理的)假设时,存在其他噪声鲁棒性机制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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