However, with an increasing weight of the regularization term, the tips of the crystal become more regular.
The regularized models produce a sequence of model fits corresponding to different values of the regularization parameter lambda.
Medina, the creator of the regularization plan, considers it a success.
Svergun, D. I. Determination of the regularization parameter in indirect-transform methods using perceptual criteria.
Typical numerical outcome of the regularization and the applicability of the obtained LS parameters are discussed.
In this approach, selection of the regularization map and the regularization parameter is very important.
We consider the limits of solutions of the regularization obtained by decreasing the critical exponent.
A range of the regularization parameter, rather than one single value, can be determined.
Guidelines for the design of the estimator structure and the selection of the regularization parameters are presented.
The iterative method successfully overcomes the difficulty of determining the optimal value of the regularization smoothing parameter.
Modifications of the regularization methods are also considered.
