 Linear regularization

A linear regularization uses a family of bounded linear operators $R_{\alpha }$ such that $R_{\alpha }f\to K^{†}f$ for each $f\in \mathcal{D}(K^{†})$. A regularization parameter choice must balance approximation error with noise amplification to obtain a convergent regularization of an inverse problem.