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This matrix is subject to a high-frequency minimization algorithm described next.
To this end, we developed the simple, greedy minimization algorithm described above.
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In the examples, the preconditioned Chambolle Pock algorithm described in [14] was used for the TV minimization.
The stereo algorithm described in this section stems from the inference principle based on hierarchical belief propagation and energy minimization.
Two local minimization methods were built: the Levenberg-Marquardt algorithm was obtained from the MINPACK subroutine LMDIF and modified to achieve the required robustness; and the Nelder-Mead simplex method has been implemented in-house based on variations of the algorithm described in the literature.
Therefore, we adopt this strategy, and our proposed interference minimization algorithm can be described in Algorithm 1.
Section 3 describes the high-frequency minimization algorithm and Section 4 describes how such compressed data are recovered through a concurrent binary search algorithm.
software package, using the steepest descent minimization algorithm in the discover module of Insight II.
The minimization algorithm takes into account already randomized patients in order to allocate a new treatment.
The cost minimization algorithm is based on graph theory and works as described in [11].
Each ligand was minimized while binding to its target protein using the in situ ligand minimization module with the following parameters: CHARMm as an input force field, minimization algorithm as smart minimizer, maximum minimization steps equal to 1000, minimization with RMS gradient equal to 0.001 Å, and minimization energy change set equal to zero.
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