An inertial projection neural network for solving inverse variational inequalities
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
| Original language | English |
|---|---|
| Pages (from-to) | 99-105 |
| Journal / Publication | Neurocomputing |
| Volume | 406 |
| Online published | 20 Apr 2020 |
| Publication status | Published - 17 Sept 2020 |
Link(s)
Abstract
A novel inertial projection neural network (IPNN) is proposed for solving inverse variational inequalities (IVIs) in this paper. It is shown that the IPNN has a unique solution under the condition of Lipschitz continuity and that the solution trajectories of the IPNN converge to the equilibrium solution asymptotically if the corresponding operator is co-coercive. Finally, several examples are presented to illustrtae the effectiveness of the proposed IPNN.
Research Area(s)
- Inertial projection neural networks, Inverse variational inequalities, Convergence analysis
Citation Format(s)
An inertial projection neural network for solving inverse variational inequalities. / Ju, Xingxing; Li, Chuandong; He, Xing et al.
In: Neurocomputing, Vol. 406, 17.09.2020, p. 99-105.
In: Neurocomputing, Vol. 406, 17.09.2020, p. 99-105.
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
