Exponential stability of a class of complex-valued neural networks with time-varying delays

This paper studies a class of complex-valued neural networks with time-varying delays. By using the conjugate system of the complex-valued neural networks and Brouwer¿s fixed point theorem, sufficient conditions to guarantee the existence and uniqueness of an equilibrium are obtained. Some criteria on globally exponential stability of the equilibrium of the complex-valued neural networks are also established by using a delay differential inequality. These results are easy to apply to the study of the complex-valued neural networks whether their activation functions are explicitly expressed by separating their real and imaginary parts or not. Two examples with numerical simulations are given to highlight the effectiveness of the obtained results.