DocumentCode
3494490
Title
A training algorithm for SpikeProp improving stability of learning process
Author
Toshiki, Wakamatsu ; Haruhiko, Takase ; Hiroharu, Kawanaka ; Shinji, Tsuruoka
Author_Institution
Grad. Sch. of Eng., Mie Univ., Tsu, Japan
fYear
2011
fDate
July 31 2011-Aug. 5 2011
Firstpage
951
Lastpage
955
Abstract
In this paper, we aims to improve stability of learning processes by the SpikeProp algorithm. We proposed the method that reduce the increase of the error in learning processes. It repeats two steps: (1) original SpikeProp algorithm, and (2) use a linear search in the steepest descent direction only if the first step is failed. Some experimental results shows the improvement of learning processes.
Keywords
feedforward neural nets; learning (artificial intelligence); stability; SpikeProp algorithm; SpikeProp network; feed-forward networks; learning process; spiking neural networks; stability improvement; supervised learning algorithm; training algorithm; Biological neural networks; Iris; Iris recognition; Mathematical model; Neurons; Surges; Training;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks (IJCNN), The 2011 International Joint Conference on
Conference_Location
San Jose, CA
ISSN
2161-4393
Print_ISBN
978-1-4244-9635-8
Type
conf
DOI
10.1109/IJCNN.2011.6033325
Filename
6033325
Link To Document