Nair, M. T.; Tautenhahn, U.
July 2008
Computational Methods in Applied Mathematics;2008, Vol. 8 Issue 3, p279
Academic Journal
For solving linear ill-posed problems with noisy data regularization methods are required. We analyze a simplified regularization scheme in Hilbert scales for operator equations with nonnegative self-adjoint operators. By exploiting the operator monotonicity of certain functions, order-optimal error bounds are derived that characterize the accuracy of the regularized approximations. These error bounds have been obtained under general smoothness conditions.


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