Interactive Learning Neural Networks for Predicting Game Behavior
ISNN '09 Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks
A new projection-based neural network for constrained variational inequalities
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
A delayed projection neural network for solving linear variational inequalities
IEEE Transactions on Neural Networks
Information Sciences: an International Journal
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on game theory
A discrete-time neural network for optimization problems with hybrid constraints
IEEE Transactions on Neural Networks
Neural networks for solving second-order cone constrained variational inequality problem
Computational Optimization and Applications
Analog neural network approach for source localization using time-of-arrival measurements
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part II
Recurrent networks for compressive sampling
Neurocomputing
Information Sciences: an International Journal
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This paper presents a recurrent neural-network model for solving a special class of general variational inequalities (GVIs), which includes classical VIs as special cases. It is proved that the proposed neural network (NN) for solving this class of GVIs can be globally convergent, globally asymptotically stable, and globally exponentially stable under different conditions. The proposed NN can be viewed as a modified version of the general projection NN existing in the literature. Several numerical examples are provided to demonstrate the effectiveness and performance of the proposed NN