An Extension of ε-Insensitive Hebbian Learning to Form a Non-Interfering Basis.

  1. Fyfe, Colin 1
  2. Corchado, Emilio 1
  1. 1 Applied Computational Intelligence Research Unit, The University of Paisley, Scotland
Revista:
International Journal of Computational Intelligence and Applications

ISSN: 1469-0268,  1757-5885

Año de publicación: 2003

Volumen: 03

Número: 03

Páginas: 281-296

Tipo: Artículo

DOI: 10.1142/S1469026803001002 GOOGLE SCHOLAR

Otras publicaciones en: International Journal of Computational Intelligence and Applications

Resumen

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.

Referencias bibliográficas

  • 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