Solution properties of Ill-posed problem in adjustment and resolution of regularization parameter;

This paper presents a variational approach using adaptive regularization parameter for keeping the information of edges and denoising largely.

This paper studies the problem of solving the regularization parameters in the regularization method and puts forward a new method for solving the regularization parameters, which uses genetic algorithms based on the generalized cross-validation criterion .

This paper makes further researches on the Gradient Regularization method, and not only establishes a fresh iterative gradient regularization algorithm in a brief way but also gives a practical way to choose regularization parameters.

To overcome over-smoothed impedance model edge,we introduce the geologic structures constraints of layers and faults which be achieved by adjusting regularization parameters at layer interfaces and faults.

A method for selecting an optimal cost parameter C in support vector machine(SVM) is presented.

As to the compact operator equation with mutual perturbation in abstract space, through a choice of regular parameter, we give a kind of majorized regular solution by the regular model.

Adaptive selection of regularization parameter in image restoration;

Applying Particle Swarm Optimization algorithm to select regularization parameter

At the same time,the method to choose regularization parameter adaptively is given.

A variational model with two adaptive regularization parameters according to the different orientions, which constructed through the characters of different kinds of pixel in a noisy image, is presented for adaptively noisy image restoration.