Synchronization and association in a large network of coupled Chua's circuits†

This work presents the results of simulation of the fully connected networks of Chua's circuits mutually coupled by nonlinear conductances derived using the Hebbian learning rule. The network can be regarded as a generalization of the Hopfield neural network built up of chaotic units. Due to the space-time synchronization of units, the studied network exhibits the ability of pattern retrieval and decorrelation of complex input patterns.