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Spiking Neural Network Based on Cusp Catastrophe Theory

Huderek Damian, Szczęsny Szymon, Rato Raul

Foundations of Computing and Decision Sciences

2019

Vol. 44, No. 3

273--284

This paper addresses the problem of effective processing using third generation neural networks. The article features two new models of spiking neurons based on the cusp catastrophe theory. The effectiveness of the models is demonstrated with an example of a network composed of three neurons solving the problem of linear inseparability of the XOR function. The proposed solutions are dedicated to hardware implementation using the Edge computing strategy. The paper presents simulation results and outlines further research direction in the field of practical applications and implementations using nanometer CMOS technologies and the current processing mode.