DocumentCode :
3419751
Title :
The research of learning algorithm of synergetic neural network
Author :
Lu, Bin ; Tian, Yuru
Author_Institution :
Sch. of Control & Comput. Eng., North China Electr. Power Univ., Baoding, China
fYear :
2012
fDate :
24-26 Aug. 2012
Firstpage :
1308
Lastpage :
1310
Abstract :
Due to existing wide consistency between synergetic thought and neural network in associative memory, learning and pattern recognition, a new network called synergetic neural network arises at the historic moment which is different form the design method of traditional neural network .In the synergetic neural network, learn also is the study of weight matrix in a given training sample set. It´s learning problems can be summed up in how to evaluate the adjoint vector and prototype vector. Learning algorithm of synergetic neural network has a lot of kinds, each one has its unique advantages and disadvantages, On the basis of introduces the principle of the synergetic neural network ,this paper analyzed the selection of prototype pattern and the solving of adjoint vector. Finally analysis the advantages of learning algorithm of synergetic neural network based on cluster algorithm.
Keywords :
learning (artificial intelligence); matrix algebra; neural nets; pattern clustering; vectors; adjoint vector; associative memory; cluster algorithm; learning algorithm; pattern recognition; prototype pattern selection; prototype vector; synergetic neural network; synergetic thought; weight matrix; cluster; synergetic Theory; synergetic learning algorithm; synergetic neural network;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Information Processing (CSIP), 2012 International Conference on
Conference_Location :
Xi´an, Shaanxi
Print_ISBN :
978-1-4673-1410-7
Type :
conf
DOI :
10.1109/CSIP.2012.6309102
Filename :
6309102
Link To Document :
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