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The outcome of our investigation is a recommendation for the use of nonlinear optimization techniques that minimize a fairness functional based on the variation of curvature.
For feedback control of the spherical motor, the quadratic form of the torque model requires the use of nonlinear optimization schemes for computing the stator coil current inputs.
In addition, since MLE makes use of nonlinear optimization in the presence of a nonlinear likelihood function such as in radio positioning, parameter initialization is required, which can be a difficult issue.
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Particular emphasis is placed on the role of nonlinear optimization techniques – e.g. convex optimization, nonsmooth calculus, proximal point and descent algorithms – as valuable tools for analyzing and solving Ky Fan inequalities.
These data are then used to fit the model by minimizing an objective function applying a variety of nonlinear optimization tools [ 17].
After joining the faculty, Kuhn collaborated on the emerging fields of nonlinear optimization and game theory.
It requires the identification of a full dynamic model of the multivariable system, and uses constrained nonlinear optimization techniques to find the controller parameters.
They are then merged into a single metric which is minimized over the set of 20 test utterances using a nonlinear optimization technique.
It does not apply to thermodynamically based algorithms such as QPMEME, MatrixREDUCE and TherMoS, which use nonlinear optimization on a continuous space of affinity models.
Using the nonlinear optimization algorithm we explored the possibility of altering enzyme concentrations to direct the fluxes to a single terminal glycan.
We use standard constrained nonlinear optimization solvers (e.g., active-set and interior point) available in the MATLAB Optimization Toolbox [ 4].
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