A new view on regularization theory

The paper provides a new viewpoint on regularization theory from different perspectives. It is shown that the regularized solution can be derived from the Fourier transformation operator in the transformation domain and with equivalent form from the linear differential operator in the spatial domain. The state-of-the-art research in regularization is briefly reviewed with extended discussions on Occam´s razor, minimum length description, Bayesian framework, pruning algorithms, statistical learning theory, and equivalent regularization