Spurious correlation as an approximation of the mutual information between redundant outputs and an unknown input
Spurious correlation as an approximation of the mutual information between redundant outputs and an unknown input
复制标题
DOI：
10.1016/j.cnsns.2014.03.021
复制
发表时间：
2014-10
期刊：
影响因子：
--
通讯作者：
Shuhei Ikemoto;F. D. Libera;K. Hosoda;H. Ishiguro
中科院分区：
文献类型：
--
作者：
Shuhei Ikemoto;F. D. Libera;K. Hosoda;H. Ishiguro
随机共振（SR）是一种反直觉的现象，在各种各样的非线性系统中都可以观察到，在这些系统中加入适当大小的噪声可以改善信号的检测。调节噪声以使SR效应最大化对人工系统和生物系统都很重要。在人工系统的情况下，充分利用SR效应开启了测量其他不可测量信号的可能性。在生物学中，识别可能的SR最大化机制对于解释在动物中经常观察到的低能量高灵敏度感知能力具有重要意义。文献中提出的SR最大化方法利用输入信号（或生物刺激）的知识，最大化输入和输出信号之间的相互信息。然而，在许多实际情况下，输入信号是未知的。为了解决这一问题，本文引入了一种基于冗余单元间伪相关的输入输出互信息近似方法。给出了近似的证明，并给出了应用的数值实例。
Stochastic resonance (SR) is a counterintuitive phenomenon, observed in a wide variety of nonlinear systems, for which the addition of noise of opportune magnitude can improve signal detection. Tuning the noise for maximizing the SR effect is important both for artificial and biological systems. In the case of artificial systems, full exploitation of the SR effect opens the possibility of measuring otherwise unmeasurable signals. In biology, identification of possible SR maximization mechanisms is of great interest for explaining the low-energy high-sensitivity perception capabilities often observed in animals. SR maximization approaches presented in literature use knowledge on the input signal (or stimulus, in the case of living beings), and maximize the mutual information between the input and the output signal. The input signal, however, is unknown in many practical settings. To cope with this problem, this paper introduces an approximation of the input–output mutual information based on the spurious correlation among a set of redundant units. A proof of the approximation, as well as numerical examples of its application are given.