记忆电阻器
神经形态工程学
人工神经网络
人工神经元
计算机科学
冯·诺依曼建筑
微带线
拓扑(电路)
电子工程
人工智能
电气工程
工程类
操作系统
作者
Lin Hai-dan,Yiran Shen
出处
期刊:Micromachines
[Multidisciplinary Digital Publishing Institute]
日期:2023-01-28
卷期号:14 (2): 337-337
被引量:1
摘要
The neuromorphic network based on artificial neurons and synapses can solve computational difficulties, and its energy efficiency is incomparable to the traditional von Neumann architecture. As a new type of circuit component, nonvolatile memristors are very similar to biological synapses in structure and function. Only one memristor can simulate the function of a synapse. Therefore, memristors provide a new way to build hardware-based artificial neural networks. To build such an artificial neural network, in addition to the artificial synapses, artificial neurons are also needed to realize the distribution of information and the adjustment of synaptic weights. As the VO2 volatile local active memristor is complementary to nonvolatile memristors, it can be used to simulate the function of neurons. However, determining how to better realize the function of neurons with simple circuits is one of the current key problems to be solved in this field. This paper considers the influence of distribution parameters on circuit performance under the action of high-frequency and high-speed signals. Two Mott VO2 memristor units are connected and coupled with microstrip lines to simulate the Hodgkin–Huxley neuron model. It is found that the proposed memristor neuron based on microstrip lines shows the characteristics of neuron action potential: amplification and threshold.
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