Residential College | false |
Status | 已發表Published |
Finding the capacity of Fuzzy neural networks (FNNs) via its equivalent fully connected neural networks (FFNNs) | |
Wang J.1; Wang C.-H.2; Chen C.L.P.1 | |
2011-09-27 | |
Conference Name | IEEE International Conference on Fuzzy Systems (FUZZ 2011) |
Source Publication | IEEE International Conference on Fuzzy Systems |
Pages | 2193-2198 |
Conference Date | JUN 27-30, 2011 |
Conference Place | Taipei, TAIWAN |
Abstract | The capacity of Fuzzy Neural Network (FNN) is explored in this paper. The FNN is first transformed into an equivalent fully connected three layer neural network, or FFNN, via a new approach proposed in this paper. Then the lower and upper bounds of FNN can be found. To check the validity of the theoretical bounds, an example is illustrated with the trainings to yield excellent capacity matching with the theoretical bounds. This new finding has its emerging values in all engineering applications using FNN, such as intelligent adaptive control, pattern recognition, and signal processing,⋯, etc. © 2011 IEEE. |
Keyword | Back Propagations Capacity Of Neural Networks Fuzzy Logic Fuzzy Neural Networks Neural Networks Universal Approximation Theorem |
DOI | 10.1109/FUZZY.2011.6007473 |
URL | View the original |
Language | 英語English |
WOS ID | WOS:000295224300329 |
Scopus ID | 2-s2.0-80053056934 |
Fulltext Access | |
Citation statistics | |
Document Type | Conference paper |
Collection | DEPARTMENT OF COMPUTER AND INFORMATION SCIENCE |
Affiliation | 1.Universidade de Macau 2.National Chiao Tung University Taiwan |
First Author Affilication | University of Macau |
Recommended Citation GB/T 7714 | Wang J.,Wang C.-H.,Chen C.L.P.. Finding the capacity of Fuzzy neural networks (FNNs) via its equivalent fully connected neural networks (FFNNs)[C], 2011, 2193-2198. |
APA | Wang J.., Wang C.-H.., & Chen C.L.P. (2011). Finding the capacity of Fuzzy neural networks (FNNs) via its equivalent fully connected neural networks (FFNNs). IEEE International Conference on Fuzzy Systems, 2193-2198. |
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