Nevertheless, we tried optimizing the L1-regularized error function E1 for regularization constant c ranging from 0 to 10 in increments of 0.1.
The integral is computed with a regularized kernel and corrections are added for regularization and discretization, which are found from analysis near the singular point.
Investigation of an expected-squared- error loss criterion reveals the need for regularization.
And for years, immigrants have been forcing their way into French churches, government offices and universities, refusing to leave without guarantees that they will be considered for "regularization".
The cost function is utilized as the new penalty term for regularization algorithms.
A method based on concerned performance is proposed for regularization of the reliability index constraints.
Sufficient linear matrix inequalities (LMIs) conditions for regularization of uncertain singular fractional-order systems are given.
Furthermore, the Levenberg Marquardt algorithm, used for regularization, is modified to enhance its numerical performance.
We propose to combine two approaches for regularization of the inverse problem.
We design a manufactured solution and demonstrate that the adaptive-basis optimization algorithm reduces the need for regularization.
Furthermore, the present method avoids additional cost to globally reinitialize the level set function for regularization purpose.
