dc.contributor.authorNguyen, Minh Nhuten_US
dc.date.accessioned2008-09-17T09:04:05Z
dc.date.accessioned2017-07-23T08:28:24Z
dc.date.available2008-09-17T09:04:05Z
dc.date.available2017-07-23T08:28:24Z
dc.date.copyright2008en_US
dc.date.issued2008
dc.identifier.citationNguyen, M. N. (2008). Ying-yang approach to the optimization of fuzzy cerebellar model articulation controller.Doctoral thesis, Nanyang Technological University, Singapore.
dc.identifier.urihttp://hdl.handle.net/10356/2493
dc.description.abstractThe Cerebellar Model Articulation Controller (CMAC) neural network has attractive properties of fast learning speed and simple computation, but its rigid structure is a disadvantage. Our research aims at the fuzzification phase and the rule weighting process to improve FCMAC by Bayesian Ying-Yang (BYY) learning, coevolution computation, and online learning.en_US
dc.rightsNanyang Technological Universityen_US
dc.subjectDRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
dc.titleYing-Yang approach to the optimization of fuzzy cerebellar model articulation controlleren_US
dc.typeThesisen_US
dc.contributor.schoolSchool of Computer Engineeringen_US
dc.contributor.supervisorShi Damingen_US
dc.description.degreeDOCTOR OF PHILOSOPHY(SCE)en_US


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