Existence, uniqueness and stability analysis of recurrent neural networks with time delay in the leakage term under impulsive perturbations

In this paper, a class of recurrent neural networks with time delay in the leakage term under impulsive perturbations is considered. First, a sufficient condition is given to ensure the global existence and uniqueness of the solution for the addressed neural networks by using the contraction mapping theorem. Then, we present some sufficient conditions to guarantee the existence, uniqueness and global asymptotic stability of the equilibrium point by using topological degree theory, Lyapunov–Kravsovskii functionals and some analysis techniques. The proposed results, which do not require the boundedness, differentiability and monotonicity of the activation functions, can be easily checked via the linear matrix inequality (LMI) control toolbox in MATLAB. Moreover, they indicate that the stability behavior of neural networks is very sensitive to the time delay in the leakage term. In the absence of leakage delay, the results obtained are also new results. Finally, two numerical examples are given to show the effectiveness of the proposed results.