Design of NbO<sub><i>x</i></sub> memristive neuron and its application in spiking neural networks

Author:

Gu Ya-Na,Liang Yan,Wang Guang-Yi,Xia Chen-Yang, ,

Abstract

NbO<sub><i>x</i></sub> memristors show great application prospect in neuromorphic computing due to its nanoscale size, threshold switching, and locally active properties. The in-depth analysis and study of NbO<sub><i>x</i></sub> memristors’s dynamic properties are beneficial to the design and optimization of memristive neuron circuits. In this paper, based on the local active theory, the physical model of NbO<sub><i>x</i></sub> memristor is studied by using the small signal analysis method, and the region and conditions of the peak oscillation are quantitatively analyzed, and the quantitative relationship between the excitation signal amplitude and the peak frequency is determined. Based on the above theoretical analysis, NbO<sub><i>x</i></sub> memristor neurons are further designed and combined with the memristive synaptic crisscross array in order to construct a 25×10 spiking neural network (SNN). Finally, the recognitional function of digital 0 to 9 patterns is effectively realized by using frequency coding and time coding respectively.

Publisher

Acta Physica Sinica, Chinese Physical Society and Institute of Physics, Chinese Academy of Sciences

Subject

General Physics and Astronomy

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