DocumentCode
1582958
Title
A Study on How to Help Back-propagation Escape Local Minimum
Author
Chai, Shaobin ; Zhou, Yong
Author_Institution
Dalian Univ. of Technol., Dalian
Volume
1
fYear
2007
Firstpage
64
Lastpage
68
Abstract
One peculiarity impairing the performance of back-propagation is the presence of local minimum. In this paper, a local minimum detection algorithm called LMD is advocated. LMD bases on two kinds of constraint of local minimum to detect and escape local minimum. Before back-propagation trapping into local minimum, LMD will take measure to rectify the adjusting method of weights and biases. Combining LMD, back-propagation is improved to LMDBP algorithm in this paper. Results of experiment of back-propagation and LMDBP indicate that LMDBP can escape local minimum much more sufficiently than back-propagation algorithm.
Keywords
backpropagation; adjusting method; backpropagation escape local minimum algorithm; backpropagation trapping; Backpropagation; Detection algorithms; Feedforward neural networks; Feedforward systems; Genetic algorithms; Mathematics; Neural networks; Software algorithms; Software performance;
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Computation, 2007. ICNC 2007. Third International Conference on
Conference_Location
Haikou
Print_ISBN
978-0-7695-2875-5
Type
conf
DOI
10.1109/ICNC.2007.150
Filename
4344155
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