title: Exponential Stability and Stabilization of Delayed Memristive Neural Networks Based on Quadratic Convex Combination Method.
abstract: This paper is concerned with the exponential stability and stabilization of memristive neural networks (MNNs) with delays. First, we present some generalized double-integral inequalities, which include some existing inequalities as their special cases. Second, combining with quadratic convex combination method, these double-integral inequalities are employed to formulate a delay-dependent stability condition for MNNs with delays. Third, a state-dependent switching control law is obtained for MNNs with delays based on the proposed stability conditions. The desired feedback gain matrices are accomplished by solving a set of linear matrix inequalities. Finally, the feasibility and effectiveness of the proposed results are tested by two numerical examples.
authors.forename: Zhanshan
authors.initials: Z
authors.lastname: Wang
authors.forename: Sanbo
authors.initials: S
authors.lastname: Ding
authors.forename: Zhanjun
authors.initials: Z
authors.lastname: Huang
authors.forename: Huaguang
authors.initials: H
authors.lastname: Zhang