基于SOA的光子脉冲LIF神经元研究
Research of the photon pulse LIF neurons based on SO A
薛利梅 1魏艳龙 1杨潞霞 1阴桂梅 1马会芳 2韩丙辰2
作者信息
- 1. 太原师范学院计算机科学与技术学院,山西晋中 030600;智能优化计算与区块链技术山西省重点实验室,山西晋中 030600
- 2. 太原师范学院物理系,山西晋中 030600;智能优化计算与区块链技术山西省重点实验室,山西晋中 030600
- 折叠
摘要
脉冲神经网络与传统人工神经网络相比,具有硬件友好性和低能耗的优点.而光子脉冲神经网络与电脉冲神经网络相比具有速度快、能耗低、传输容量大和抗电磁干扰能力强等优点.基于半导体光放大器(SOA)设计了一种新的光子脉冲神经元模型—LIF(泄漏积分与发射)模型,实现了信号的加权、延迟、积分和阈值判决等功能,并在此基础上探索了该LIF模型在数字逻辑中的应用.实现了基于该模型的"异或"逻辑功能,并改进了一种具有兴奋性和抑制性神经元,通过光通信仿真软件得到LIF模型、"异或"逻辑和具有兴奋性和抑制性神经元良好的输出.
Abstract
Compared with the traditional artificial neural network,pulse neural network has the advantages of hardware-friendliness and low energy consumption.Compared with the electric pulse neural network,the photon pulse neural network has the advantages of high speed,low energy consumption,large transmission capacity and strong anti-electromagnetic interference ability.Based on the semiconductor optical amplifier(SOA),a new neuron model of photon pulse-LIF(leakage integration and fire)model is designed in this paper,and the application of LIF model in digital logic is explored.The"XOR"logic function based on the model is realized,and an excitatory and inhibitory neuron is improved,LIF model,XOR logic and good output of excitatory and inhibitory neurons were obtained by opti-cal communication simulation software.
关键词
光通信/全光逻辑/LIF神经元(leakage/integration/and/fire)/光子脉冲神经元Key words
optical communication/all-optical logic/LIF neurons(leakage integration and fire)/photon pulse neurons引用本文复制引用
基金项目
山西省科技战略研究专项(202204031401114)
山西省青年科学研究项目(202203021212185)
山西省重点研发计划(202102010101008)
出版年
2024
NETL
NSTL
万方数据