多层前馈神经网络信号放大的研究

项目名称： 多层前馈神经网络信号放大的研究

项目编号： No.11305078

项目类型： 青年科学基金项目

立项/批准年度： 2014

项目学科： 数理科学和化学

项目作者： 梁晓明

作者单位： 江苏师范大学

项目金额： 22万元

中文摘要： 信号放大是生物神经系统的一项重要功能，但是何种神经网络结构支持这一功能尚未清楚。已知的工作集中在由单稳态神经元构成的单层神经网络，忽视了真实神经网络的两个重要特点：层级结构和神经元双稳性。前者是指信号在处理过程中会依次经过不同的功能层，后者则指负责信号处理的部分神经元存在两个稳定的休息态。鉴于此，本项目拟提出一种由双稳态神经元构成的多层前馈神经网络，其中信号由输入层输入，经若干中间层单向传输至输出层输出。通过研究多层前馈结构和神经元双稳性对信号放大的影响，找出在何种网络条件下输入的信号会在输出层放大输出，其目的在于提出一种基于网络拓扑结构和神经元自身特性的信号放大机制。进一步，项目还将从噪声以及网络中部分神经元病死入手研究信号放大机制的鲁棒性。本项目的研究可加深对网络功能与网络结构之间关系的理解，也可为认识生物的信号放大本领提供新思路。

中文关键词： 信号放大；前馈模体；双稳态；相位噪声；生物节律

英文摘要： The ability of amplifying weak signals is a fundamental mechanism of nervous systems. However, which neural network structure supports such amplification is not well known yet. Previous studies have paid more attention to the single layer neural networks constituted by monostable neurons, ignoring two important features of real neural networks: multilayer feedforward structure and neuronal bistability. The former means signals are unidirectional processed through different functional layers in neural networks, while the latter denotes that certain types of neurons participating signal processing exhibit two stable resting states. Based on these two features, this project aims to propose a specific type of neural networks constituted by bistable neurons with multilayer feedforward structure, in which the signal is processed only in one direction starting from the first input layer and arriving at the final output layer via a series of intermediate layers. Based on the multilayer feedforward neural networks, the project examines the impacts of the multilayer feedforward structure and neuronal bistability on signal amplification so as to figure out the conditions under which a weak input signal could be amplified in the output layer, thereby proposing a new mechanism of signal amplification which only relies on the

英文关键词： signal amplification；feedforward motif；bistable state；phase noise；circadian rhythms