DocumentCode
2647779
Title
On the extent of simplifications in backpropagation training equations
Author
Bahrami, Mohammad
Author_Institution
Sch. of Electr. Eng., New South Wales Univ., Sydney, NSW, Australia
fYear
1994
fDate
29 Nov-2 Dec 1994
Firstpage
18
Lastpage
21
Abstract
Usually the simplified form of the backpropagation training equations are used instead of the original equations for training of neural networks. The validity of these simplifications and the extent to which these methods can operate is explored. It is shown that although these methods can reduce the time and complexity of computations carried out during training, their effectiveness is problem dependent
Keywords
backpropagation; computational complexity; neural nets; backpropagation training equations; neural network training; problem dependent effectiveness; simplified form; Australia; Backpropagation; Computational complexity; Decoding; Differential equations; Helium; Intelligent networks; Mars; Multilayer perceptrons; Neural networks;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Information Systems,1994. Proceedings of the 1994 Second Australian and New Zealand Conference on
Conference_Location
Brisbane, Qld.
Print_ISBN
0-7803-2404-8
Type
conf
DOI
10.1109/ANZIIS.1994.396958
Filename
396958
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