DocumentCode :
2678396
Title :
Research on grouping-cascaded BP network model
Author :
Zhiyong Lu ; Chaojing Tang
Author_Institution :
Coll. of Electron. Sci. & Eng., Nat. Univ. of Defense Technol., Changsha, China
Volume :
5
fYear :
2010
fDate :
27-29 March 2010
Firstpage :
425
Lastpage :
429
Abstract :
To resolve the training problem of high dimension BP neural network with limited small samples, this paper puts forward the concept of loosely and tightly grouping-cascaded BP network model, the definition of equivalence with BP neural network, and relative theorem. On the base of constructing the grouping-cascaded model which is proved equivalent to BP network, the required training sample numbers of two kinds of neural network models are compared. Finally, the feasibility and validity of the proposed grouping-cascaded BP network model are verified with simulation results.
Keywords :
backpropagation; cascade networks; neural nets; BP neural network; grouping cascaded BP network model; grouping cascaded model; Chaos; Educational institutions; Equations; Fault diagnosis; Feedforward neural networks; Feedforward systems; Minimization methods; Multi-layer neural network; Neural networks; Target recognition; BP neural networks; equivalent; grouping-cascaded network model; small samples;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Computer Control (ICACC), 2010 2nd International Conference on
Conference_Location :
Shenyang
Print_ISBN :
978-1-4244-5845-5
Type :
conf
DOI :
10.1109/ICACC.2010.5487075
Filename :
5487075
Link To Document :
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