A novel chaotic spiking neuron and its paralleled spike encoding function

Authors:
Hiroyuki Torikai;Tom Nishigami
Affiliations:
Graduate School of Engineering Science, Osaka University, Japan;Graduate School of Engineering Science, Osaka University, Japan
Venue:
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Year:
2009

Citing 4
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2009 Special Issue: An artificial chaotic spiking neuron inspired by spiral ganglion cell: Paralleled spike encoding, theoretical analysis, and electronic circuit implementation

Neural Networks

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Abstract

Inspired by sound encoding mechanisms of the spiral ganglion cell in the mammalian inner ear, in this paper we present a novel chaotic spiking neuron and analyze its encoding function. A set of N neurons accepts a common analog input and outputs a set of N chaotic spike-trains. We give some theorems which guarantee that the set of neurons can encode various inputs (which can be constant, periodic, nonperiodic or random) into a summation of their spike-trains in such a way that a spike density of the summed spike-train mimics a waveform of the input. We also confirm the encoding function of an electrical circuit model of the neuron by a SPICE simulation.