Novel Stability Criteria for Impulsive Memristive Neural Networks with Time-Varying Delays

Abstract

In order to improve the ability of resisting disturbance for memristive neural networks (MNNs), a general impulsive controlled MNN with variable delays is constructed in this paper. Then, its dynamical behaviors are investigated based on the differential inclusion theories. By constructing suitable Lyapunov---Krasovskii-type functional and combining with integral and monotone function method, the global exponential stability criteria of delayed memristive neural networks (DMNNs) with impulse effects are derived. Furthermore, the impulsive controlled DMNNs can be transformed to DMNNs without impulsive effects, which promote and enrich the theoretical research results of MNNs. Finally, the effectiveness of obtained results is illustrated by two numerical examples.