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In multidimensions, reducing the order of a solution can save significant amounts of computer time.
Therefore, an L filter model could be used to control the fundamental frequency components by reducing the order of the final controller.
The effects of minimizing computational complexities on signal representation by reducing the order of the transform and the overlap length between signal segments are also examined.
In addition to reducing the order of the state problem, the maximum filter reduces the order of the optimization problem to increase computational efficiency.
It is shown that the proposed set of base vectors forms an excellent candidate for reducing the order of the equations of motion.
The method is based on simple iterative schemes which are formed by reducing the order of the momentum equation and by rearranging the resulting non-linear equations into a system of linear equations.
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To reduce the order of polynomials on each element, nonconforming elements are an attractive option.
These λ-symmetries can be used to reduce the order of equation.
To reduce the order of identification, we discretize these variables with each time-period (0.5 h).
Moreover, tuning functions are designed to reduce the order of the parameter updater.
This discontinuity can significantly reduce the order of accuracy of the numerical scheme.
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CEO of Professional Science Editing for Scientists @ prosciediting.com