DocumentCode :
2618763
Title :
An accelerated back propagation training algorithm
Author :
Kothari, Ravi ; Klinkhachorn, Powsiri ; Nutter, Roy S.
Author_Institution :
Dept. of Electr. & Comput. Eng., West Virginia Univ., Morgantown, WV, USA
fYear :
1991
fDate :
18-21 Nov 1991
Firstpage :
165
Abstract :
The concept of backpropagation training with a gradual increase in accuracy is presented. The concept may be incorporated with the basic backpropagation algorithm or with the backpropagation algorithm with a momentum weight change to result in significant speed improvements without increasing the size of the network or requiring additional support hardware. Experimental results show that the proposed modification, on the average, doubles the convergence rate of the backpropagation algorithm and the backpropagation algorithm with a momentum weight change
Keywords :
convergence; learning systems; neural nets; accelerated back propagation training algorithm; convergence rate; learning systems; momentum weight change; neural nets; Acceleration; Convergence; Dynamic range; Multi-layer neural network; Neural network hardware; Neural networks; Neurons; Robustness;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1991. 1991 IEEE International Joint Conference on
Print_ISBN :
0-7803-0227-3
Type :
conf
DOI :
10.1109/IJCNN.1991.170398
Filename :
170398
Link To Document :
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