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Unformatted text preview: loglog(lam,errs) xlabel('\lambda') ylabel('error') title(' Tikhonov regularization applied to the Hilbert matrix ') [emin kmin]=min(errs) emin emin = lam(kmin) ans = 1.52E-012 % We see the minimum error is .0023 - since the norm of % the ones vector is sqrt(60) the minimum relative error % is about 3X10^(-4) - Extremely good as the error without % regularization is more than 100% % % The best choice for lambda is about 1.5X10^(-12) % % We see that by using Tikhonov regularization we could % accurately find a ``nice'' solution to a highly ill-conditioned % problem....
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- Spring '09