Learning by optimization in random neural networks

Atalay V.

13th International Symposium on Computer and Information Sciences (ISCIS 98), BELEK ANTALYA, Turkey, 26 - 28 October 1998, vol.53, pp.143-148 identifier

  • Publication Type: Conference Paper / Full Text
  • Volume: 53
  • City: BELEK ANTALYA
  • Country: Turkey
  • Page Numbers: pp.143-148
  • Middle East Technical University Affiliated: Yes

Abstract

The random neural network model proposed by Gelenbe has a number of interesting features in addition to a well established theory. Gelenbe has also developed a learning algorithm for the recurrent random network model using gradient descent of a quadratic error function. We present a quadratic optimization approach for learning in the random neural network, particularly for image texture reconstruction.