Autors: Kirilov, S. M., Mladenov, V. M.
Title: LTSPICE Memristor Neuron with a Modified Transfer Function Based on Memristor Model with Parasitic Parameters †
Keywords: LTSPICE memristor models, memristor modeling, memristor-based neuron, MOS transistor-memristor transfer function, parasitic parameters

Abstract: Memristors, as novel one-port electronic elements, have very good memory and commutating properties, insignificant power consumption, and a good compatibility to present CMOS integrated chips. They are applicable in neural networks, memory arrays, and various electronic devices. This paper proposes a simple LTSPICE model of an adapted activation function and a neuron built on memristors. In the neuron, synaptic bonds are implemented by single memristors, allowing a decreased circuit complexity. The summing and scaling schemes are based on op-amps and memristors. The applied modified tangent-sigmoidal activation function is implemented with MOS transistors and memristors. Analyses and simulations are conducted using a simple and high-rate operating memristor model with parasitic parameters—resistance, inductance, capacitance, and small-signal DC components. Their influence on the normal operation of the memristors in the neuron is analyzed, paying attention to their usage and adjustment. The proposed memristor-based artificial neuron is analyzed in MATLAB–Simulink and LTSPICE simulators. A comparison between the derived results confirms the correct operation of the proposed memristor neuron. The generation and analyses of the suggested memristor-based neuron is a significant and promising step for the design and engineering of high-complexity neural networks and their realization in ultra-high-density integrated neural circuits and chips.

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Issue

Electronics (Switzerland), vol. 14, pp. 1-20, 2025, Switzerland, https://doi.org/10.3390/electronics14234645

Вид: статия в списание, публикация в издание с импакт фактор, публикация в реферирано издание, индексирана в Scopus и Web of Science