An improved criterion for stability and attractability of memristive neural networks with time-varying delays

Memristive neural networks are a novel topic in the design and construction of brain-like circuitry system. This paper addresses a challenging problem: How to derive some less conservative theoretical results on the stability and attractability for memristive neural networks? In this paper, a new comparison method and segmentation method of state space are developed. A succinct criterion is provided to ascertain the global exponential stability and the estimate for location of equilibrium point. The obtained criterion is the improvement and extension of the existing results in the literature. The applicability of the proposed framework can be extended to general memristive neurodynamic systems.