On the conjugate gradients (CG) training algorithm of fuzzy neural networks (FNNs) via its equivalent fully connected neural networks (FFNNs)

Jing Wang*, C. L.Philip Chen, Chi-Hsu Wang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

In this paper, Fuzzy Neural Network (FNN) is transformed into an equivalent fully connected three layer neural network, or FFNN. Based on the FFNN, conjugate gradients (CG) training algorithm is derived to tune both the premise and consequent part of FNN, and apparently increase the speed of convergence. Illustrative examples are presented to check the validity of the proposed theory and algorithms. Simulation achieves satisfactory results. Developing CG training algorithm for FNN via its equivalent FFNN has its emerging values in all engineering applications using FNN, such as intelligent adaptive control, pattern recognition, and signal processing..., etc.

Original languageEnglish
Title of host publicationProceedings 2012 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2012
Pages2446-2451
Number of pages6
DOIs
StatePublished - 1 Dec 2012
Event2012 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2012 - Seoul, Korea, Republic of
Duration: 14 Oct 201217 Oct 2012

Publication series

NameConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
ISSN (Print)1062-922X

Conference

Conference2012 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2012
CountryKorea, Republic of
CitySeoul
Period14/10/1217/10/12

Keywords

  • Fuzzy Logic
  • Fuzzy Neural Networks
  • Gradient Descent
  • Neural Networks
  • conjugate gradients

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    Wang, J., Chen, C. L. P., & Wang, C-H. (2012). On the conjugate gradients (CG) training algorithm of fuzzy neural networks (FNNs) via its equivalent fully connected neural networks (FFNNs). In Proceedings 2012 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2012 (pp. 2446-2451). [6378110] (Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics). https://doi.org/10.1109/ICSMC.2012.6378110