Exponential stabiliy of neural networks with delay

In this thesis; the expnential stability of the equilibrium point of delayed neural networks was studied. In the first chapter; giving the basic properties of the exponential stability and the neural network, some results which are in the literature were introduced. In the second chapter; the basic notions and main idea about Lyapunov method were exhibited. In the third chapter; it was shown that the exponential stability of the equilibrium point of two different systems of differential equations that model delayed neural networks can be obtained by using the second method of Lyapunov. In the last chapter; for the reader to investigating the exponential stability of the equilibrium point of some equation models was advised. Keywords: Differential Equations with Delay, Exponential stability, Lyapunov function, Neural Networks