基于脉冲时间依赖可塑性的自适应神经网络抗扰能力研究

Robustness Analysis of Adaptive Neural Network Model Based on Spike Timing-Dependent Plasticity

为探究生物神经网络的自组织抗扰特性,进而为电子系统的电磁仿生防护提供新的思路和方法,本文基于神经网络中信息传递的机制和脉冲时间依赖突触可塑性(STDP)机制,探讨了突触可塑性与生物自适应特性的关系,然后选取Izhikevich神经元模型作为基本单元,以STDP机制调节的突触为桥梁,构建了四层的前馈神经网络模型,最后分析了该网络的自适应抗扰能力。仿真结果表明,基于STDP机制的神经网络具有很好的抗扰能力,且这种特性与STDP机制密切相关。基于此仿真工作将进一步进行领域转换,搭建模拟生物神经系统信息处理机制的神经元及突触的单元电路,并以该单元电路为基础设计具有自适应抗扰的电子电路。

To explore the self-organization robustness of the biological neural network,and thus to provide new ideas and methods for the electromagnetic bionic protection,we studied both the information transmission mechanism of neural network and spike timing-dependent plasticity（STDP）mechanism,and then investigated the relationship between synaptic plastic and adaptive characteristic of biology.Then a feedforward neural network with the Izhikevich model and the STDP mechanism was constructed,and the adaptive robust capacity of the network was analyzed.Simulation results showed that the neural network based on STDP mechanism had good rubustness capacity,and this characteristics is closely related to the STDP mechanisms.Based on this simulation work,the cell circuit with neurons and synaptic circuit which can simulate the information processing mechanisms of biological nervous system will be further built,then the electronic circuits with adaptive robustness will be designed based on the cell circuit.