Hanyong Shao

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This brief is concerned with the stability for static neural networks with time-varying delays. Delay-independent conditions are proposed to ensure the asymptotic stability of the neural network. The delay-independent conditions are less conservative than existing ones. To further reduce the conservatism, delay-dependent conditions are also derived, which(More)
This brief is concerned with delay-dependent stability for neural networks with two additive time-varying delay components. By constructing a new Lyapunov functional and using a convex polyhedron method to estimate the derivative of the Lyapunov functional, some new delay-dependent stability criteria are derived. These stability criteria are less(More)
This paper provides improved delay-dependent stability criteria for systems with a delay varying in a range. The criteria improve over some previous ones in that they have fewer matrix variables yet less conservatism, which is established theoretically. An example is given to show the advantages of the proposed results. © 2008 Elsevier Ltd. All rights(More)
This paper is concerned with the stability for static neural networks with time-varying delays. With an appropriate Lyapunov functional formulated, a new technique is proposed to up bound the derivative of the Lyapunov functional. A delay-dependent stability criterion is obtained by proving the bound negative definite with convex combination methods. The(More)