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A Spiking Neural Network Based on the Model of VO2–Neuron

Institute of Physics and Technology, Petrozavodsk State University, 31 Lenina str., Petrozavodsk 185910, Russia
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Electronics 2019, 8(10), 1065; https://doi.org/10.3390/electronics8101065
Received: 27 August 2019 / Revised: 13 September 2019 / Accepted: 18 September 2019 / Published: 20 September 2019
In this paper, we present an electrical circuit of a leaky integrate-and-fire neuron with one VO2 switch, which models the properties of biological neurons. Based on VO2 neurons, a two-layer spiking neural network consisting of nine input and three output neurons is modeled in the SPICE simulator. The network contains excitatory and inhibitory couplings, and implements the winner-takes-all principle in pattern recognition. Using a supervised Spike-Timing-Dependent Plasticity training method and a timing method of information coding, the network was trained to recognize three patterns with dimensions of 3 × 3 pixels. The neural network is able to recognize up to 105 images per second, and has the potential to increase the recognition speed further. View Full-Text
Keywords: leaky integrate-and-fire neuron; vanadium dioxide; neural network; pattern recognition leaky integrate-and-fire neuron; vanadium dioxide; neural network; pattern recognition
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Belyaev, M.; Velichko, A. A Spiking Neural Network Based on the Model of VO2–Neuron. Electronics 2019, 8, 1065.

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