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The fully discretized finite element equations are obtained by approximating the convolution integrals using a trapezoidal rule.
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To calculate the integral of the convolution type, a recurrence formula is used that can be obtained by approximating the initial kernel with a linear combination of exponential functions (the truncated Prony's series).
The TTA approximates the convolution kernel for the linear response of the LNP model.
The quality of the approximation in Eq. (14) depends on how well the (sum _{k=0}^{n-1} {mathbf {A}}^k) operator is approximated by the convolution operation ({mathbf {C}}_{{mathbf {q}}_n}).
Equivalently, we can say that the delay distribution function (67) of each path of the source can be approximated by the convolution of a dominant exponential delay distribution associated with this congested node and some other negligible delay distributions which behave like weighted dirac delta functions as compared with the dominant distribution as follows: (70).
A quadrature formula for the temporal discretization is adopted to approximate the convolution integrals and a collocation method for the spatial discretization.
The present time-domain BEM uses a quadrature formula for the temporal discretization to approximate the convolution integrals and a collocation method for the spatial discretization.
Approximating the color is fine.
In this work, we used the recursive implementation of the (approximated) Gaussian convolution proposed by Young and van Vliet [44].
By employing the convolution theorem and making use of an appropriate class of approximating identities, we provide necessary axioms and define function spaces where the fractional Fourier integral operator is an isomorphism connecting the different spaces.
We denote by ∗ the convolution.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

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