Backpropagation in perceptrons with feedback
Neural Computers
Neural network for quadratic optimization with bound constraints
IEEE Transactions on Neural Networks
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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 delay-dependent stability criterion is simpler and less conservative than some existing ones. Both delay-independent and delay-dependent criteria are obtained, which can be checked easily using the recently developed algorithms. Examples are provided to illustrate the effectiveness and the reduced conservatism of the proposed results.