尖峰神经网络
计算机科学
记忆电阻器
生物神经元模型
神经形态工程学
突触
人工神经网络
脉搏(音乐)
信号(编程语言)
人工智能
电子工程
神经科学
电信
探测器
工程类
生物
程序设计语言
作者
Wenwu Jiang,Jie Li,Hongbo Liu,Xicong Qian,Yuan Ge,Lidan Wang,Shukai Duan
出处
期刊:Chinese Physics B
[IOP Publishing]
日期:2022-03-01
卷期号:31 (4): 040702-040702
被引量:4
标识
DOI:10.1088/1674-1056/ac380b
摘要
Spiking neural networks (SNNs) are widely used in many fields because they work closer to biological neurons. However, due to its computational complexity, many SNNs implementations are limited to computer programs. First, this paper proposes a multi-synaptic circuit (MSC) based on memristor, which realizes the multi-synapse connection between neurons and the multi-delay transmission of pulse signals. The synapse circuit participates in the calculation of the network while transmitting the pulse signal, and completes the complex calculations on the software with hardware. Secondly, a new spiking neuron circuit based on the leaky integrate-and-fire (LIF) model is designed in this paper. The amplitude and width of the pulse emitted by the spiking neuron circuit can be adjusted as required. The combination of spiking neuron circuit and MSC forms the multi-synaptic spiking neuron (MSSN). The MSSN was simulated in PSPICE and the expected result was obtained, which verified the feasibility of the circuit. Finally, a small SNN was designed based on the mathematical model of MSSN. After the SNN is trained and optimized, it obtains a good accuracy in the classification of the IRIS-dataset, which verifies the practicability of the design in the network.
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