System identification using neural network with parametric sigmoid function

M. Hasheminejad, J. Murata, K. Hirasawa

Research output: Contribution to conferencePaper

Abstract

Nonlinear systems can be modeled by neural networks. However choice of suitable network architecture is the most important problem. And 'how to find the best activation function' is a persistent aspect of the architecture design. Here we have proposed a sigmoid function with one parameter which provides us not only the reduction of error bound but also the opportunity of obtaining better insight into the systems.

Original languageEnglish
Pages39-44
Number of pages6
Publication statusPublished - Dec 1 1994
EventProceedings of the Artificial Neural Networks in Engineering Conference (ANNIE'94) - St. Louis, MO, USA
Duration: Nov 13 1994Nov 16 1994

Conference

ConferenceProceedings of the Artificial Neural Networks in Engineering Conference (ANNIE'94)
CitySt. Louis, MO, USA
Period11/13/9411/16/94

All Science Journal Classification (ASJC) codes

  • Engineering(all)

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    Hasheminejad, M., Murata, J., & Hirasawa, K. (1994). System identification using neural network with parametric sigmoid function. 39-44. Paper presented at Proceedings of the Artificial Neural Networks in Engineering Conference (ANNIE'94), St. Louis, MO, USA, .