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To demonstrate the performance of our proposed design, we apply our approach for the tuning problem of Support Vector Machines.
Regarding controller design, we apply a hierarchical and decentralised synthesis method from earlier work in order to achieve nonblocking and safe closed-loop behaviour.
Then, for the boundary control design, we apply the control parameterization method to obtain an approximate optimal parameter selection problem that can be solved using nonlinear optimization techniques such as Sequential Quadratic Programming (SQP).
We consider identification in given 3 or 4 measurement occasions in the classical twin design, we apply the model to data obtained at 4 occasions.
We follow the same line of thought: given a combinatorial design we apply weighting to each pool separately and randomly, while limiting the number of weights to a small number in order to facilitate fast computation and optimization.
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For the robust control design purpose, we apply decentralized sliding-mode control the stability of which can be easily verified using Lyapunov theory.
In another structure design, we applied the optical model to graphene back contacted CdS/CdTe device.
In order to simplify the design, we applied a factorial analysis to the 40 competences.
Study Design: We applied the transcolumellar approach, which modified the external rhinoplasty approach on the 136 cases of transsphenoidal pituitary surgery that were performed from 1994 to June 1999.
Study design: We applied a spatio-temporal analysis to EEG recordings of a group of neonates to investigate the influence of a cesarean section on maturation and extrauterine adaptation of the brain.
In a randomized sham-controlled, double-blinded parallel design, we applied 20 min of tDCS over the supplementary motor area (SMA) and prefrontal cortex (PFC) while subjects performed a DBT.
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CEO of Professional Science Editing for Scientists @ prosciediting.com