Sentence examples for minimize f with from inspiring English sources

Because the functional (17) only contains an unknown variable ϕ, we can simply minimize F with respect to ϕ.

The final F-NMF update rules to minimize f with all these considerations are derived from (6), (9), (11), (13), (15), and (17).

The VNE-ABC algorithm attempts to find the best solution (i.e., the solution with the lowest fitness) for each request to minimize f(X).

But minimizing the last expression with respect to f is equivalent to minimizing f ↦ γ ˜ ( f ) with γ ˜ ( f ) = − 2 ∑ m = 1 M ∫ T 1 T 2 ψ t ( m ) ( f ) λ ( m ) ( t ) d t + ∑ m = 1 M ∫ T 1 T 2 [ ψ t ( m ) ( f ) ] 2 d t.

Consider the convex minimization problem (CMP) of minimizing f over the constraint set C, minimize  { f ( x ) : x ∈ C }. (1.4).

Now, we have minimized F As before etching to less than F As<1×10−8 Torr during a 1-h growth interruption with the As cell switched off.

Define the optimization problem as: Minimize f (X).

Based on the analysis in above sections, we reformulate the blind reconstruction problem with ℓ p -norm (0 < p < 1) minimization approach as minimize r f | | r f | | p s.t.

More specifically, suppose that S is the finite set of all possible solutions and f is a real valued function (i.e., the OF), defined on members of S. The problem is to find a solution s ∈ S that minimizes f over S. The algorithm starts with an initial solution.

( SP − ⪯ )  ⪯-minimize F ( x ), subject to x ∈ X, with some given preorder ⪯ and a set-valued objective map F : X ⇉ Y, we can see the following.

In this case the problem is to choose a configuration x0 that minimizes f(x) or makes it ε = minimal that is, for any number ε > 0, f(x0) f(x) + ε, for all configurations x, with the specified properties.