A Regularized Gradient Projection Method for the Minimization Problem
We investigate the following regularized gradient projection algorithm xn+1=Pc(I−γn(∇f+αnI))xn, n≥0. Under some different control conditions, we prove that this gradient projection algorithm strongly converges to the minimum norm solution of the minimization problem minx∈Cf(x).
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2012-01-01
|
| Series: | Journal of Applied Mathematics |
| Online Access: | http://dx.doi.org/10.1155/2012/259813 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | We investigate the following regularized gradient projection
algorithm xn+1=Pc(I−γn(∇f+αnI))xn, n≥0. Under some different control conditions, we prove that this gradient projection algorithm
strongly converges to the minimum norm solution of the minimization problem minx∈Cf(x). |
|---|---|
| ISSN: | 1110-757X 1687-0042 |