Models of neural networks with fuzzy activation functions

International Conference on Mechanical Engineering, Automation and Control Systems 2016

机械制造;无线电电子学;计算机科学

Nguyen, A.T.^1 ; Korikov, A.M.^1,2

Tomsk Polytechnic University, Lenina Ave., 30, Tomsk

634050, Russia^1

Tomsk State University of Control Systems and Radioelectronics, Lenina Ave., 40, Tomsk

634050, Russia^2

关键词: Activation functions;    Fuzzy inference systems;    Fuzzy membership function;    Fuzzy neural network model;    Neuron activation function;    Neuron model;    Property predictions;    Time-dependent signals;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/177/1/012031/pdf
DOI  :  10.1088/1757-899X/177/1/012031

学科分类：计算机科学（综合）

来源: IOP

【 摘 要 】

This paper investigates the application of a new form of neuron activation functions that are based on the fuzzy membership functions derived from the theory of fuzzy systems. On the basis of the results regarding neuron models with fuzzy activation functions, we created the models of fuzzy-neural networks. These fuzzy-neural network models differ from conventional networks that employ the fuzzy inference systems using the methods of neural networks. While conventional fuzzy-neural networks belong to the first type, fuzzy-neural networks proposed here are defined as the second-type models. The simulation results show that the proposed second-type model can successfully solve the problem of the property prediction for time - dependent signals. Neural networks with fuzzy impulse activation functions can be widely applied in many fields of science, technology and mechanical engineering to solve the problems of classification, prediction, approximation, etc.