|Apr7-10, 07:32 AM||#1|
Numerical Optimization ( steepest descent method)
1. The problem statement, all variables and given/known data
Consider the steepest descent method with exact line searches applied to the
convex quadratic function f(x) = 1/2 xT Qx − bT x, ( T stands for transpose). show that if the initial point is such that x0 − x* ( x* is the exact solution of Qx = b) is parallel to an eigenvector of Q, then the steepest descentmethod will find the solution in one step.
2. Relevant equations
3. The attempt at a solution.
I tried to find a relation between the eigenvector and the given initial point but I couldn't
|Similar Threads for: Numerical Optimization ( steepest descent method)|
|Using the method of steepest descent||Calculus & Beyond Homework||3|
|Steepest descent contour includes singularity (asymptotic expansions)||Calculus & Beyond Homework||0|
|Steepest descent, non-analytic roots||Calculus||1|
|Question on the Method of Steepest Decent||Calculus||2|