A study of chaos neural network with a periodic activation function

We put forward a novel chaos neuron model and investigate its dynamic properties. The artificial neuron model is defined by such periodic input-output mapping as a sinusoidal function. It is obviously shown that the present neural network has the ability of embedded pattern retrieval in the neural network beyond the conventional one with a monotonous mapping such as the signum function. This advantage is considered to be as a result of the nonmonotonous property of the periodic mapping which involves the chaotic behaviour of the neurons. It is also found that the present chaos neuron model has a remarkably larger memory capacity than the conventional association system with the monotonous dynamics