There have been a lot of researches which apply evolutionary techniques to layered neural networks. However, their applications to Hopfield neural networks remain few so far. We are applying genetic algorithms to fully connected associative memory model of Hopfield. In an earlier paper, we reported that random weight matrices were evolved to store some number of patterns only by means of a simple genetic algorithm. In this paper we present that the storage capacity can be enlarged by incorporating Lamarckian inheritance to the genetic algorithm.
|Number of pages||5|
|Publication status||Published - Jan 1 1996|
|Event||Proceedings of the 1996 IEEE International Conference on Evolutionary Computation, ICEC'96 - Nagoya, Jpn|
Duration: May 20 1996 → May 22 1996
|Other||Proceedings of the 1996 IEEE International Conference on Evolutionary Computation, ICEC'96|
|Period||5/20/96 → 5/22/96|
All Science Journal Classification (ASJC) codes