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Only in some cases, when the analytic expressions of the constraint and objective functions are available (which is not the case in this paper), more simple methods can be derived with polynomial complexity but still assuring optimality.
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In Section 3, some new reduction formulas for the linearization coefficients of some Jacobi polynomials are derived with the aid of employing some symbolic algebraic computation such as the algorithms of Zeilberger, Petkovsek and van Hoeij, hence four new linearization formulas for products of some nonsymmetric Jacobi polynomials are also given in this section.
In this paper, the EVM expression of a multicarrier signal distorted by a polynomial PA model is derived with or without the use of a clipping technique.
However, the forward models can be derived to univariate polynomial equations with different orders: 8th for pattern I and 4th for pattern II.
The selected sets of observations and the derived polynomial fits for each selected data set are shown along with the polynomial order and the coefficient of determination, R2, giving an indication of the goodness of the fit in each case.
This schema also allows the computation of numerical derivatives considering the coefficient of the derived polynomial.
It is straightforward to estimate the frequency of a triploid genotype with genotype observations using (1) which is derived from a polynomial likelihood.
To avoid numerical instability, coefficients for the quintic polynomials were derived using Chebyshev polynomials The two sequences determining the horizontal and vertical migration of a laboratory spot are the two sequences associated with its matching virtual spot.
The derived polynomial equations were verified by check point formulation.
The derived polynomial equation and contour graph aid in predicting the values of selected independent variables for preparation of optimum nanosuspension formulations with desired properties.
The derived polynomial equation and contour graph aid in predicting the values of selected independent variables for preparation of optimum nanoemulsion with desired properties.
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