Global asymtotic stability of integro differential equation systems modeling delayed neural networks

In this thesis; the global asymptotic stability of the equilibrium point of delayed neural networks was studied. In the first chapter; the basic properties of the global asymptotic stability and the neural network were given. In the second chapter; some results which are in the literature were introduced. In the third chapter; the basic notions and main idea about Lyapunov method were exhibited. In the fourth chapter; it was shown that the global asymptotic 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 global asymptotic stability of the equilibrium point of some equation models was advised.