[1]ZHANG Xiu-ling,LI Shao-qing,TIAN Li-yong.Research of flatness pattern recognition based on the Elman neural network[J].CAAI Transactions on Intelligent Systems,2010,5(5):449-453.[doi:10.3969/j.issn.1673-4785.2010.05.012]
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Research of flatness pattern recognition based on the Elman neural network

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 5 Number of periods: 2010 5 Page number: 449-453 Column: 学术论文—机器感知与模式识别 Public date: 2010-10-25
Title:
Research of flatness pattern recognition based on the Elman neural network
Author(s):
ZHANG Xiu-ling1; 2;  LI Shao-qing1; 2;  TIAN Li-yong1; 2
1.College of Electrical Engineering, Yanshan University， Qinhuangdao 066004, China; 2.Key Laboratory of Industrial Computer Control Engineering of Hebei Province, Yanshan University, Qinhuangdao 066004, China
Keywords:
flatness pattern recognition;  Elman neural network;  dynamic network
CLC:
TP183
DOI:
10.3969/j.issn.1673-4785.2010.05.012
Abstract:
Due to the presently poor level of designing and recognizing time patterns and generalizations of static neural networks, as well as the fact that learning speed is slow, a flatness pattern recognition system based on the Elman neural network was presented. The system is simple and efficient, because of its philosophy of over-learning or over-fitting a neural network and determining the number of the hidden nodes with experiential formulas and contrasting experiments. This system has generalization capability through learning the six basic flatness patterns and their combinations. The simulation shows that each error of actual output is less than 0.1, giving a good result, and that the capability of the system based on the Elman dynamic network pattern recognition is better than the system based on a BP network.
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Last Update: 2010-11-26

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