Spiking Neural Network Based on Cusp Catastrophe Theory

IF 1.8 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Foundations of Computing and Decision Sciences Pub Date : 2019-09-01 DOI:10.2478/fcds-2019-0014
Damian Huderek, S. Szczȩsny, R. Rato
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引用次数: 6

Abstract

Abstract 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.
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基于尖点突变理论的脉冲神经网络
本文研究了利用第三代神经网络进行有效处理的问题。本文介绍了基于尖峰突变理论的两种新的尖峰神经元模型。通过一个由三个神经元组成的网络解决异或函数线性不可分问题的实例,验证了该模型的有效性。提出的解决方案专门用于使用边缘计算策略的硬件实现。本文给出了仿真结果,并概述了纳米CMOS技术在实际应用和实现领域的进一步研究方向以及当前的加工模式。
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来源期刊
Foundations of Computing and Decision Sciences
Foundations of Computing and Decision Sciences COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-
CiteScore
2.20
自引率
9.10%
发文量
16
审稿时长
29 weeks
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