Abstract
The gradient method for the symmetric positive definite linear system Ax=b is as follows xk + 1=xk- αkgkwhere gk=Axk-b is the residual of the system at xkand αkis the stepsize. The stepsize alphak= 2/λ1+λnis optimal in the sense that it minimizes the modulus ||I - α A||2, where λ1and λnare the minimal and maximal eigenvalues of A respectively. Since λ1and λnare unknown to users, it is usual that the gradient method with the optimal stepsize is only mentioned in theory. In this paper, we will propose a new stepsize formula which tends to the optimal stepsize as k → ∞. At the same time, the minimal and maximal eigenvalues, λ1and λn, of A and their corresponding eigenvectors can be obtained.
Original language | English |
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Pages (from-to) | 73-88 |
Number of pages | 16 |
Journal | Computational Optimization and Applications |
Volume | 33 |
Issue number | 1 |
DOIs | |
Publication status | Published - 1 Jan 2006 |
Keywords
- (Shifted) power method
- Gradient method
- Linear system
- Steepest descent method
ASJC Scopus subject areas
- Control and Optimization
- Computational Mathematics
- Applied Mathematics