DocumentCode :
1566244
Title :
Fast learning neural network with modified neurons
Author :
Hwang, Rey-Chue ; Chen, Yu-Ju ; Shang-Jen Chuang ; Huang, Huang-Chu ; Chang, Wei-Chang
Author_Institution :
Electr. Eng. Dept., I-Shou Univ., Kaohsiung, Taiwan
Volume :
1
fYear :
2005
Firstpage :
313
Abstract :
In this paper, a neural model with modified neurons is developed. Compare with traditional neural network, such a neural model not only has a fast learning, but also can significantly improve the accuracy while it is used in real applications. To demonstrate the learning efficiency of neural model we developed, a nonlinear system identification problem is studied and simulated. All simulations are performed by using constant learning rates (0.1∼0.9). From the simulation results, the neural model we developed obviously has excellent performances as desired.
Keywords :
identification; learning (artificial intelligence); neural nets; nonlinear systems; fast learning neural network; modified neurons; nonlinear system identification; Adaptive systems; Iterative algorithms; Learning systems; Neural networks; Neurons; Power system modeling; Process control; Programmable control; Signal processing; Signal processing algorithms; accuracy; fast learning; modified neurons; neural model;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Technology and Applications, 2005. ICITA 2005. Third International Conference on
Print_ISBN :
0-7695-2316-1
Type :
conf
DOI :
10.1109/ICITA.2005.144
Filename :
1488818
Link To Document :
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