Silicon neuron: digital hardware implementation of the quartic model View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2014-11

AUTHORS

F. Grassia, T. Levi, T. Kohno, S. Saïghi

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. More... »

PAGES

215-219

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10015-014-0160-2

DOI

http://dx.doi.org/10.1007/s10015-014-0160-2

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1022400020


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