The regularized algorithms of statistical estimation of functions

The regularized algorithms of filtration are supported and investigated. Hereby optimal of the information point of view M-parametric approximations of required function are used. The approximation parameters are determined by a maximum likelihood method. The number of parameters is defined by $\chi^2$ criterion. The results of 1D and 2D modeling problems are represented.