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Spiking Neuron Network Based on VTEAM Memristor and MOSFET-LIF Neuron

Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT,volume 659)

Abstract

Neuromorphic computing has been widely developed due to its low power consumption and powerful interpretability. LIF neurons, the general-purpose neurons in neuromorphic computing, are under constant research in hardware implementations of spiking neural networks. In this paper, we design a LIF circuit with MOSFET based on the mathematical model of the LIF neuron. The simulated circuit can be directly applied to the spiking neural network through the VTEAM memristor crossbar architecture. The effect of parameter changes in the circuit on the membrane potential is demonstrated. Finally, we validate feasibility of the process on the DVS128 gesture dataset using a generic spiking neural network architecture and obtain satisfactory performance.

Keywords

This research was funded by the Natural Science Foundation of Shaanxi Province (Grant No. 2022JQ-661) and the Fundamental Research Funds for the Central Universities (Grant No. XJS222215).

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Correspondence to Zhang Guo .

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Fu, J., Gou, S., Guo, Z. (2022). Spiking Neuron Network Based on VTEAM Memristor and MOSFET-LIF Neuron. In: Shi, Z., Jin, Y., Zhang, X. (eds) Intelligence Science IV. ICIS 2022. IFIP Advances in Information and Communication Technology, vol 659. Springer, Cham. https://doi.org/10.1007/978-3-031-14903-0_5

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  • DOI: https://doi.org/10.1007/978-3-031-14903-0_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-14902-3

  • Online ISBN: 978-3-031-14903-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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