Sentence examples for minimization can obtain from inspiring English sources

Thus, we may reasonably infer that there exits a q 0 ≤ 0.1 such that for any q < q 0, all the l 2/l q <span class="lh">minimization can obtain similar recovery results when the noise level is low ( σ = 0.02,0.05); while there exits a q 0 ≤ 0.7 such that as q < q 0 decreases, the mixed l 2/l q  method is unable to improve the recovery results when σ = 0.10.

Minimizing (1/2)‖ w‖ is equal to maximizing the margin, and minimizing C∑ i L ξ i can obtain the minimization of the classification error.

Equation (13) indicates that the minimization of energy function (13) can obtain the correct object segmentation of.

with zero mean and a variance of σ n 2. Thus, we can obtain a new minimization problem with the Meridian prior assumption, abbreviated as MMP, MMP J x = ln f n y − Ω x + ln f x = ln γ Q Π i = 1 Q 1 + x i b − 2 + ln exp − y − Ω x 2 2 σ n 2 = − 2 γ Q ∑ i = 1 Q ln 1 + x i b − y − Ω x 2 2 σ n 2 x ^ MAP = arg min x J x = arg min x ∑ i = 1 Q ln 1 + x i b + β y − Ω x 2 2, β = 1 2 γ Q σ n 2. (7).

It has been shown that the optimal solution of ℓ0 minimization can be obtained by solving ℓ1 minimization under certain conditions (e.g., restricted isometry property or RIP) [2 6].

The proposed investigation procedure is a synthetic analysis concerning optimization of both Ψ and its components Ψh and Ψf, via which the dominating compartment and the key impact factors for irreversibility minimization can be obtained as a guidance for practical design of rotating helical tube heat exchangers.

These observation models have been described in Section 2. The minimization of energy functional (15) by curve evolution can obtain a stationary global minimum.

In Theorem 4.3 taking (B=I) and (H_{2}=H_{3}), from Theorem 4.3 we can obtain the following convergence theorem for split convex minimization problem (1.14) (SCMP phi,varphi)).

They often formulate the non-convex l 1 minimization problem and solve the problem by alternating directions method of multipliers (ADMM) [15], which can obtain a suboptimal solution to the non-convex problem.

Weight minimization can also be considered or the minimization of the electric voltages applied in the piezoelectric actuators.

The cycle is repeated until no further minimization can be achieved.