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This paper is concerned with impulsive Cohen-Grossberg-type BAM neural networks with time-varying delays and reaction-diffusion terms. By delay differential inequality with impulses, we present some sufficient conditions ensuring the global exponential stability of the equilibrium point. A numerical example is given to demonstrate the effectiveness and applicability of the proposed criteria.
It is a trouble thing to build theoretical model for stir characteristics of screw axis with variable diameters and different pitches, so a called PSO-BP neural network (NN) model was employed. In this mode, particle swarm optimization (PSO) algorithm is used to train weights and thresholds of artificial neural network instead of BP algorithm, to overcome drawbacks of BP algorithm. To avoid the slow...
In this paper, the artificial neural network (ANN) algorithm for solving system of linear equations is considered and the algorithm convergence theorem is derived. Some numerical tests are given to demonstrate the effectiveness of our results.
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