用于神经形态电路仿真的挥发性TiO₂忆阻器的端到端建模
End-to-End Modeling of a Volatile TiO2 Memristor for Neuromorphic Circuit Simulation
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中文总结 AI 辅助
本研究针对挥发性TiO₂忆阻器开发了端到端仿真模型，经SPICE验证可精准复现其电学行为，可用于神经形态电路级仿真。
中文摘要 AI 辅助
忆阻器是一类极具应用前景的器件，可应用于非易失性存储器、神经形态计算、逻辑电路以及模拟信号处理等领域。这类系统的开发需要基于模型的精准仿真，该模型需能复现真实器件在连续激励与脉冲激励下的电学行为。本研究开发了针对基于TiO₂的挥发性忆阻器的仿真环境，分析实验测量数据以验证该器件的忆阻行为并确定合适的模型，随后优化模型参数以匹配测量特性。将所得模型在SPICE中实现，通过对比仿真结果与测量数据进行验证，结果显示仿真与实验具有良好一致性，表明所开发的模型适用于复现所研究忆阻器的电学行为，且可应用于电路级仿真，这一点通过漏极积分放电神经元得到了验证。
英文摘要
Memristors are promising devices for applications such as non-volatile memory, neuromorphic computing, logic circuits, and analog signal processing. The development of such systems requires accurate simulations based on models that reproduce the electrical behavior of real devices under both continuous and pulsed excitation. This work presents the development of a simulation environment for a volatile TiO2-based memristor. Experimental measurement data are analyzed to verify the memristive behavior of the device and to identify a suitable model. The model parameters are then optimized to match the measured characteristics. The resulting model is implemented in SPICE and validated by comparing simulation results with measurement data. The comparison shows a good agreement between simulation and experiment, demonstrating that the developed model is suitable for reproducing the electrical behavior of the investigated memristor and can be applied in circuit-level simulations, as demonstrated by a leaky integrate-and-fire neuron.
