Two universally applicable smoothing operations adjustable to meet the specific properties of the given smoothing problem are widely used: 1. Smoothing splines and 2. Smoothing digital convolution filters. The first operation is related to the data vector $r={(r_0,...,r_{n-1})}^T$ with respect to the operations $𝒜$, $ℒ$ and to the smoothing parameter $\alpha$. The resulting function is denoted by ${\sigma }_{\alpha }\left(t\right)$. The measured sample $r$ is defined on an equally spaced mesh $\Delta ={\{t_i=ih\}}_{i=0}^{n-1}$$...$