Design of General Projection Neural Networks for Solving Monotone Linear Variational Inequalities and Linear and Quadratic Optimization Problems

@article{Hu2007DesignOG,
  title={Design of General Projection Neural Networks for Solving Monotone Linear Variational Inequalities and Linear and Quadratic Optimization Problems},
  author={Xiaolin Hu and Jun Wang},
  journal={IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics)},
  year={2007},
  volume={37},
  pages={1414-1421}
}
Most existing neural networks for solving linear variational inequalities (LVIs) with the mapping Mx + p require positive definiteness (or positive semidefiniteness) of M. In this correspondence, it is revealed that this condition is sufficient but not necessary for an LVI being strictly monotone (or monotone) on its constrained set where equality… CONTINUE READING