A product-of-norms model for recurrent neural networks
Jiaying Hou, F.M.A. Salam · 2003
The authors present a model for recurrent artificial neural networks which can store any number of any prespecified patterns as energy local minima. Therefore, all the prespecified patterns can be stored and retrieved. The authors summarize the model's stability properties. They then give two examples, showing how this model can be used in image recognition and association.>