Abstract
Synchronization is introduced into a chaotic neural network model to discuss its associative memory. The relative time of synchronization
of trajectories is used as a measure of pattern recognition by chaotic
neural networks. The retrievability of memory is shown to be connected
to synapses, initial conditions and storage capacity. The technique is
simple and easy to apply to neural systems.