An Extension of ε-Insensitive Hebbian Learning to Form a Non-Interfering Basis.
- Fyfe, Colin 1
- Corchado, Emilio 1
- 1 Applied Computational Intelligence Research Unit, The University of Paisley, Scotland
ISSN: 1469-0268, 1757-5885
Year of publication: 2003
Volume: 03
Issue: 03
Pages: 281-296
Type: Article
More publications in: International Journal of Computational Intelligence and Applications
Abstract
We review an extension of Hebbian learning which has been called ε-Insensitive Hebbian Learning (Fyfe and MacDonald, 2001) and derive lateral connections from a probability density function. We use these lateral connections to move outputs towards the mode of the pdf and use the resulting outputs to train the feedforward connections. We show that the resulting network is able to identify a single orientation of bars from a mixture of horizontal and vertical bars.
Bibliographic References
- Fyfe C., Neuro Comput.
- 10.1142/S0129065789000475
- 10.1088/0954-898X_7_2_006
- 10.1088/0954-898X_9_2_002
- 10.1016/S0893-6080(05)80107-8
- Bishop C. M., (1995), Neural Networks for Pattern Recognition
- 10.1016/0893-6080(94)90060-4
- Seung H. S., Adv. Neural Inf. Process. Syst., 10
- Bertsekas D. P., (1995), Nonlinear Programming
- 10.1023/A:1009606706736