Sparse Regularization with $l^q$ Penalty Term

Abstract

We consider the stable approximation of sparse solutions to non-linear operator equations by means of Tikhonov regularization with a subquadratic penalty term. Imposing certain assumptions, which for a linear operator are equivalent to the standard range condition, we derive the usual convergence rate $O(\sqrt{\delta })$ of the regularized solutions in dependence of the noise level $\delta$. Particular emphasis lies on the case, where the true solution is known to have a sparse representation in a given basis. In this case, if the differential of the operator satisfies a certain injectivity condition, we can show that the actual convergence rate improves up to $O(\delta )$.

15 pages

References in corpus (2)

• Convergence rates and source conditions for Tikhonov regularization with sparsity constraints
• A Semismooth Newton Method for Tikhonov Functionals with Sparsity Constraints

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