Global exponential stability of Clifford-valued recurrent neural networks

This paper investigates global exponential stability of a class of Clifford-valued recurrent neural networks. By using Brouwer's fixed point theorem, the existence of the equilibrium point of Clifford-valued recurrent neural networks is studied. A sufficient condition of global exponential stability is given by the method of the Clifford-valued variation parameter and inequality technique. Compared with the previous methods, our method does not resort to any Lyapunov function which is not easy to construct. (C) 2015 Elsevier B.V. All rights reserved.