A Flexible Memristor Model With Electronic Resistive Switching Memory Behavior and Its Application in Spiking Neural Network
A Flexible Memristor Model With Electronic Resistive Switching Memory Behavior and Its Application in Spiking Neural Network
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DOI：
10.1109/tnb.2022.3152228
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发表时间：
2023-01-01
影响因子：
3.9
通讯作者：
Lai, Loi Lei
中科院分区：
文献类型：
--
作者：
Ji, Xiaoyue;Lai, Chun Sing;Lai, Loi Lei
忆阻技术因其非易失性、高密度、低功耗以及与 CMOS 的兼容性而颇具吸引力。对于忆阻器件来说，与实际行为特征相对应的模型非常有利于其神经形态系统和应用的实现。本文提出了一种具有电子电阻切换存储行为的新型柔性忆阻器模型。首先，采用水热合成法和磁控溅射法制备了Ag-Au$/$MoSe2掺杂Se$/$Au-Ag忆阻器，并在电化学工作站上进行了性能测试。然后，构建了Ag-Au$/$MoSe2掺杂Se$/$Au-Ag忆阻器的数学模型和SPICE电路模型。通过使用性能测试获得的电化学数据来验证模型的准确性。此外，该模型还应用于具有生物机制的尖峰神经网络的电路实现。最后进行计算机仿真和分析，验证整个方案的有效性和有效性。
Memristive technologies are attractive due to their non-volatility, high-density, low-power and compatibility with CMOS. For memristive devices, a model corresponding to practical behavioral characteristics is highly favorable for the realization of its neuromorphic system and applications. This paper presents a novel flexible memristor model with electronic resistive switching memory behavior. Firstly, the Ag-Au $/$ MoSe2-doped Se $/$ Au-Ag memristor is prepared using hydrothermal synthesis method and magnetron sputtering method, and its performance test is conducted on an electrochemical workstation. Then, the mathematical model and SPICE circuit model of the Ag-Au $/$ MoSe2-doped Se $/$ Au-Ag memristor are constructed. The model accuracy is verified by using the electrochemical data derived from the performance test. Furthermore, the proposed model is applied to the circuit implementation of spiking neural network with biological mechanism. Finally, computer simulations and analysis are carried out to verify the validity and effectiveness of the entire scheme.