標題: On the Conjugate Gradients (CG) Training Algorithm of Fuzzy Neural Networks (FNNs) via Its Equivalent Fully Connected Neural Networks (FFNNs)
作者: Wang, Jing
Chen, C. L. Philip
Wang, Chi-Hsu
電機工程學系
Department of Electrical and Computer Engineering
關鍵字: Neural Networks;Fuzzy Logic;Fuzzy Neural Networks;Gradient Descent;conjugate gradients
公開日期: 1-一月-2012
摘要: 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
URI: http://hdl.handle.net/11536/146339
ISSN: 1062-922X
期刊: PROCEEDINGS 2012 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC)
起始頁: 2446
結束頁: 2451
顯示於類別:會議論文