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Silicon neuron: digital hardware implementation of the quartic model

Abstract : This paper presents an FPGA implementation of the quartic neuron model. This approach uses digital computation to emulate individual neuron behavior. We implemented the neuron model using fixed point arithmetic operation. The neuron model's computations are performed in arithmetic pipelines. It was designed in VHDL language and simulated prior to mapping in the FPGA. We show that the proposed FPGA implementation of the quartic neuron model can emulate the electrophysiological activities in various types of cortical neurons and is capable of producing a variety of different behaviors, with diversity similar to that of neuronal cells. The neuron family of this digital neuron can be modified by appropriately adjusting the neuron model's parameters.
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Contributor : Timothée Levi <>
Submitted on : Friday, March 7, 2014 - 7:15:50 AM
Last modification on : Tuesday, March 17, 2020 - 11:16:02 AM
Long-term archiving on: : Saturday, June 7, 2014 - 10:50:12 AM


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  • HAL Id : hal-00956628, version 1


Filippo Grassia, Timothée Levi, Takashi Kohno, Sylvain Saïghi. Silicon neuron: digital hardware implementation of the quartic model. International Symposium on Artificial Life and Robotics, Jan 2014, Beppu, Japan. pp.359-362. ⟨hal-00956628⟩



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