We consider iterative methods for solving linear ill-posed problems with compact operator and right-hand side only available via noise-polluted measurements. Conjugate gradients () applied to the normal equations with an appropriate stopping rule and applied to the system solving for a Tikhonov-regularized solution () (A^ A + c Iₗ) x^ (δ, c) = A^ y^δ are closely related regularization methods that build iterates from the same family of Krylov subspaces. In this work, we show that the iterate can be expressed as x^ (δ, c) ₘ = ₈=₁^m γ^ (m) ᵢ (c) zᵢ^ (m) vᵢ, where γᵢ^ (m) (c) ₈=₁ᵐ are functions of the Tikhonov parameter and x^ (δ) ₘ = ₈=₁^m zᵢ^ (m) vᵢ is the m-th iterate. We call these functions Lanczos filters, and they can be shown to have decay properties as c with the speed of decay increasing with i. This has the effect of filtering out the contribution of the later terms of the iterate. The filters can be constructed using quantities defined via recursions at each iteration. We demonstrate with numerical experiments that good parameter choices correspond to appropriate damping of the Lanczos vectors. The filtration approach also provides a platform for further development of parameter choice rules, and similar representations may hold for other hybrid iterative schemes.
Gerth et al. (2025) studied this question.