NDLI: Study on single input-single output of CMAC neural network

Content Provider	IEEE Xplore Digital Library
Author	Liao Zhong
Copyright Year	2010
Description	Author affiliation: College of Mechanical and Electrical Engineering, China Jiliang University, Hangzhou China (Liao Zhong)
Abstract	Considering of the real question in the conventional Cerebllar Model Articulation Controller (CMAC) neural network, a single input-single output CMAC (SISO CMAC) algorithm is studied in this paper. The direct weight address mapping techniques are used in the algorithm, and the relation between the inputs and the weights is established by taking the quantification of input x as their weight address, and the generalization capability of network is enhanced by input x normalized. The study of network uses random sample, so the network has characteristics of simple study and quick convergence and high accuracy of function approximation, etc, and implement in single chip microcomputer. In the end, it is showed the algorithm is validity by theory proved and simulation experiments.
Starting Page	4724
Ending Page	4726
File Size	285468
Page Count	3
File Format	PDF
ISBN	9781424476169
e-ISBN	9781424476183
DOI	10.1109/ICISE.2010.5691806
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-12-04
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Electrical engineering Adaptive systems Simulation Adaptation model Artificial neural networks Direct address mapping Nonlinear systems Integrated circuit modeling Cerebllar model articulation controller neural network Convergence Single input-single output
Content Type	Text
Resource Type	Article

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