Multilayer Neural Networks for Hierarchical Patterns
Nicolas Sourlas · Europhysics Letters (EPL) · 1988
We propose a new class of neural network models with multilayer architecture for storing hierarchically correlated patterns. These models are solved in the replica-symmetric approximation and it is found that their storing capacity, still linear in the number of neurons, is much larger than that of the traditional Hopfield-type models.