Abstract
The silicon neuron is an analog electronic circuit that reproduces the dynamics of a neuron. It is a useful element for artificial neural networks that work in real time. Silicon neuron circuits have to be simple, and at the same time they must be able to realize rich neuronal dynamics in order to reproduce the various activities of neural networks with compact, low-power consumption, and an easy-to-configure circuit. We have been developing a silicon neuron circuit based on the Izhikevich model, which has rich dynamics in spite of its simplicity. In our previous work, we proposed a simple silicon neuron circuit with low power consumption by reconstructing the mathematical structure in the Izhikevich model using an analog electronic circuit. In this article, we propose an improved circuit in which all of the MOSFETs are operated in the sub-threshold region.
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This work was presented in part at the 16th International Symposium on Artificial Life and Robotics, Oita, Japan, January 27–29, 2011
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Mizoguchi, N., Nagamatsu, Y., Aihara, K. et al. A two-variable silicon neuron circuit based on the Izhikevich model. Artif Life Robotics 16, 383–388 (2011). https://doi.org/10.1007/s10015-011-0956-2
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DOI: https://doi.org/10.1007/s10015-011-0956-2