Sentence examples for minimization problem has from inspiring English sources

The minimization problem has to be solved numerically.

The matrix nuclear norm minimization problem has received much attention in recent years, largely because its highly related to the matrix rank minimization problem arising from controller design, signal processing and model reduction.

Moreover, if f is, in addition, strictly convex and coercive, then the minimization problem has a unique solution.

Lagrangian relaxation-based approaches to obtain suboptimal algorithms for the weighted sum-power minimization problem has been introduced in [13, 14].

Also, the solution to the ordinary least squares minimization problem has β ^ j = 0 with zero probability, so this minimization does not perform feature selection.

We can now re-write the objective function to be minimized as: λ ∑ i = 1 n (ξ 1 i + ξ 2 i ) + 1 2 ‖ w ‖ 2. The solution to this constrained minimization problem has the form: f ^ (x ) = ∑ i = 1 n α i x i x + b (Nocedal and Wright 1999).

The topology optimization problem is reformulated as a volume minimization problem having probabilistic displacement constraints using the performance measure approach.

In a real Hilbert space, methods for solving the constrained convex minimization problem have been extensively studied.

Compared with Equation 22, the compliance minimization problem and the maximum stress minimization problem have equal optimal results in this example.

Methods for solving the equilibrium problem and the constrained convex minimization problem have extensively been studied respectively in a Hilbert space.

In a real Hilbert space, methods for solving the equilibrium problem and constrained convex minimization problem have been extensively studied, respectively.