Artificial Neuron Modelling Based on Wave Shape
Neural and Evolutionary Computing
2014-03-06 v1
Abstract
This paper describes a new model for an artificial neural network processing unit or neuron. It is slightly different to a traditional feedforward network by the fact that it favours a mechanism of trying to match the wave-like 'shape' of the input with the shape of the output against specific value error corrections. The expectation is then that a best fit shape can be transposed into the desired output values more easily. This allows for notions of reinforcement through resonance and also the construction of synapses.
Cite
@article{arxiv.1403.1073,
title = {Artificial Neuron Modelling Based on Wave Shape},
author = {Kieran Greer},
journal= {arXiv preprint arXiv:1403.1073},
year = {2014}
}
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