DocumentCode :
1625223
Title :
Fuzzy CMAC structures
Author :
Mohajeri, Kamran ; Zakizadeh, Manijeh ; Moaveni, Bijan ; Teshnehlab, Mohammad
Author_Institution :
North power Transm. Maintenance Co.y, Sari, Iran
fYear :
2009
Firstpage :
2126
Lastpage :
2131
Abstract :
Cerebellum model articulation controller (CMAC) is known as a feedforward neural network (NN) with fast learning and performance. Many improvements have been introduced to it which fuzzy CMAC (FCMAC) is the most important one. Fuzzy CMAC as a neuro fuzzy system increases precision, reduces memory size and makes CMAC differentiable. In addition FCMAC converts CMAC NN as a black box to a white box that its operation is interpretable using fuzzy rules. Fuzzy CMAC has not a unique structure in literature and there are differences in many aspects as membership function, memory layered structure, deffuzification and the fuzzy system applied. Discussing these, this paper reviews fuzzy CMAC different structures in literature.
Keywords :
cerebellar model arithmetic computers; feedforward neural nets; fuzzy neural nets; cerebellum model articulation controller; feedforward neural network; fuzzy CMAC; fuzzy rule; membership function; memory layered structure; neuro fuzzy system; Brain modeling; Computational modeling; Control systems; Feedforward neural networks; Fuzzy systems; Neural networks; Power system modeling; Power transmission; Quantization; Robot control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems, 2009. FUZZ-IEEE 2009. IEEE International Conference on
Conference_Location :
Jeju Island
ISSN :
1098-7584
Print_ISBN :
978-1-4244-3596-8
Electronic_ISBN :
1098-7584
Type :
conf
DOI :
10.1109/FUZZY.2009.5277185
Filename :
5277185
Link To Document :
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