Liang Xiaobing, Liu Xishun, Liu Anzhi, Wang Boliang
College of Electronic Science and Engineering, National University of Defense Technology, Changsha 410073, China.
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2009 Aug;26(4):912-6.
In nonlinear systems, noise can improve the responses of the systems with appropriate noise intensity. This phenomenon is called stochastic resonance. Biological neural systems are noisy and stochastic resonance has been found in them experimentally and theoretically. Now many researches focus on the signal transmission and processing in neural models. So this paper introduces the researches of stochastic resonance in noisy neural models. Then the recent research achievement and progress are reviewed in the following three aspects: noise; the development of stochastic resonance; and neural network. At last, the foreground of the study is discussed.
在非线性系统中，噪声在具有适当噪声强度的情况下可以改善系统的响应。这种现象被称为随机共振。生物神经系统存在噪声，并且已经在实验和理论上发现了其中的随机共振。现在许多研究集中在神经模型中的信号传输和处理上。因此，本文介绍了噪声神经模型中随机共振的研究。然后从以下三个方面综述了最近的研究成果和进展：噪声；随机共振的发展；以及神经网络。最后，讨论了该研究的前景。
