Sentence examples for solution norm from inspiring English sources

where η is the regularization parameter that determines the amount of penalization the solution norm undergoes.

As α increases, solution norm η = ||Lf||2 decreases, while residual norm ζ increases.

We observe that the solution norm exhibits a series of fairly constant 'plateaus' that are separated by sharp downward peaks.

This method intends to balance between two conflicting goals: minimizing the residual error norm and keeping the solution norm small.

Careful inspection reveals that the norm of the residual error r − Ψ ˜ ˜ y p 2 declines sharply at early stages, and then, it flattens while the solution norm ∥y p ∥2 increases sharply at early stages and then it flattens.

The widely used L-curve approach, which is the log log scale plot of the residual norm versus solution norm, is used to estimate the regularization parameter in this study.

The first method utilizes the residual and solution norms of the optimization problem and ensures that they are both small.

Noting that the residual and the solution norms can be written in terms of the filtering factors as [13]: r − Ψ ˜ ˜ y p 2 2 = ∑ n = 1 N 1 − f p, n u n H r 2 (29).

To find a near globally optimal solution, the norm relaxed sequential quadratic programming approach is applied to find the locally optimal solutions of this nonconvex optimization problem.

Significant accuracy gains in manufactured solution error norms are noted even with modest promotion of the underlying polynomial order.

Similar to the minimum L 2 norm solution, minimum L 1 norm solution aims at solving the following minimization problem.