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A multi-layer back propagation artificial neural network (BPNN) was used to predict the friction coefficient and the specific wear rate of short fiber reinforced polyetheretherketone (PEEK) composites. The best network structure for property forecast is decided as 5-[29]1-2. The train function is trainlm, and the transfer functions from input to hidden layers and from hidden to output layers are logsig...
This paper investigates the global asymptotic stability (GAS) for a class of nonlinear neural networks with multiple delays. Based on Lyapunov stability theory, homeomorphism and the linear matrix inequality (LMI) technique, a new sufficient condition is proposed for (i) existence (ii) uniqueness and (iii) global asymptotic stability of equilibrium point, of a class of nonlinear neural networks without...
In this paper, we consider delayed bidirectional associative memory (BAM) neural networks (NNs) with Lipschitz continuous activation functions. By applying Young's inequality and Holder's inequality techniques together with the properties of monotonic continuous functions, global exponential stability criteria are established for BAM NNs with time delays. This is done through the use of a new Lyapunov...
Without the boundedness assumption for the activation functions and without any extra constraints on variable delay functions, based on Lyapunov functional, homeomorphism map, techniques of inequalities and linear matrix inequality(LMI), a new delay-dependent stability criterion for (i) existence (ii) uniqueness and (iii) globally exponential stability of equilibrium point, of a class of discrete-time...
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