DocumentCode :
1930436
Title :
Hardware Implementation of CMAC Neural Network using FPGA Approach
Author :
Chung, Chao-Ming ; Lin, Chih-Min ; Chiang, Ching-Tsan ; Yeung, Daniel S.
Author_Institution :
Yuan Ze Univ., Tao Yuan
Volume :
4
fYear :
2007
fDate :
19-22 Aug. 2007
Firstpage :
2005
Lastpage :
2011
Abstract :
This paper proposes a hardware design and implementation of a cerebellar model articulation controller (CMAC neural network). The computer software simulation and FPGA hardware realization of CMAC neural network are developed. The Altera series FPGA chips are used to implement CMAC to achieve the characteristics of small size, fast execution speed and less memory. The system accuracy is verified through software simulation and hardware test. Two nonlinear functions and a real-time photovoltaic system are employed to illustrate the system performance. From the experimental results, it can be verified that the designed FPGA-based CMAC neural network can accurately model the nonlinear systems.
Keywords :
cerebellar model arithmetic computers; digital simulation; field programmable gate arrays; intelligent control; nonlinear systems; Altera series FPGA chips; CMAC neural network; FPGA hardware realization; cerebellar model articulation controller; computer software simulation; hardware design; hardware implementation; nonlinear functions; nonlinear systems; real-time photovoltaic system; Computational modeling; Computer networks; Computer simulation; Field programmable gate arrays; Neural network hardware; Neural networks; Photovoltaic systems; Real time systems; Software testing; System testing; CMAC; FPGA; System modeling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics, 2007 International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-0973-0
Electronic_ISBN :
978-1-4244-0973-0
Type :
conf
DOI :
10.1109/ICMLC.2007.4370476
Filename :
4370476
Link To Document :
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