The non-linear dynamics of a chaotic attractor offer a number of useful features to the developer of neuromorphic systems. Included in these is the ability for efficient memory storage and recall. A chaotic attractor has a potentially infinite number of Unstable Periodic Orbits (UPO) embedded within it. These orbits can be stabilised with the application of delayed feedback inhibition. This res...

This paper addresses the synchronization of chaotic gyros with unknown parameters and external disturbance via an adaptive dynamic neural network control ADNNC system. The proposed ADNNC system is composed of a neural controller and a smooth compensator. The neural controller uses a dynamic RBF DRBF network to online approximate an ideal controller. The DRBF network can create new hidden neuron...

In this paper, anti-synchronization problem of two identical chaotic neural networks with time-varying delays is proposed. By using time-delay feedback control technique, mean value theorem and the Leibniz-Newton formula, and by constructing appropriately Lyapunov-Krasovskii functional, sufficient condition is proposed to guarantee the asymptotically anti-synchronization of two identical chaoti...

Human brain can be regarded as a complicated multi-layers dynamical system which including plenty of chaotic neural groups. In this paper, a simplified multi-layers chaotic neural network is proposed and found that its dynamical characteristics are more complexity than those in a neural group through computer simulation.

Inspired by the information processing of human neural systems, the artificial neural networks (ANNs) have been developed and applied to solve problems in various disciplines with varying degrees of success. For example, ANNs have been applied to memory storage, pattern recognition, categorization, error correction, decision making, and machine learning in object oriented machine. Various compu...