Solving convex quadratic programming problems by an modified neural network with exponential convergence
Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45) › 32_Refereed conference paper (with ISBN/ISSN) › peer-review
Author(s)
Detail(s)
| Original language | English |
|---|---|
| Title of host publication | Proceedings of 2003 International Conference on Neural Networks and Signal Processing, ICNNSP'03 |
| Pages | 306-309 |
| Volume | 1 |
| Publication status | Published - 2003 |
| Externally published | Yes |
Publication series
| Name | |
|---|---|
| Volume | 1 |
Conference
| Title | 2003 International Conference on Neural Networks and Signal Processing, ICNNSP'03 |
|---|---|
| Place | China |
| City | Nanjing |
| Period | 14 - 17 December 2003 |
Link(s)
Abstract
This paper presents using a modified neural network with exponential convergence to solve strictly quadratic programming problems with general linear constraints. It is shown that the proposed neural network is globally convergent to a unique optimal solution within a finite time. Compared with the existing the primal-dual neural network and the dual neural network for solving such problems, the proposed neural network has a low complexity for implementation and can be guaranteed to have a exponential convergence rate. © 2003 IEEE.
Citation Format(s)
Solving convex quadratic programming problems by an modified neural network with exponential convergence. / Xia, Yousben; Feng, Gang.
Proceedings of 2003 International Conference on Neural Networks and Signal Processing, ICNNSP'03. Vol. 1 2003. p. 306-309 1279271.Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45) › 32_Refereed conference paper (with ISBN/ISSN) › peer-review
