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We analyze the numerical behavior of these limiters applied to a pair of model problems, comparing the error of the approximate solutions, and discuss each limiter's advantages and disadvantages.
The error of the approximate solution is monotone deceasing in the sense of (Vert.Vert _{W_2^{(1,1)}}).
Here, we introduce a process for estimating the error of the approximate solution, i.e. (e_{M}(x)=y(x -y_{M}(x -y_{
(3.15) The solution (varepsilon_{h}^{2}) of system (3.14) is the error of the approximate solution obtained by the finite difference method for problem (3.1) when on the boundary nodes (Gamma_{jh}), the approximate values are defined as the exact values of the functions (Phi _{j}) in (3.1).
(45) The solution (epsilon_{h}^{2}) of system (44) is the error of the approximate solution obtained by the finite difference method for problem (30), when the boundary values satisfy the conditions begin{aligned}& Psi_{j} in C^{4,lambda}(gamma_{j}),quad 0< lambda <1, j=1,2,3,4, end{aligned} (46) begin{aligned}& Psi_{j}^{(2q)}(s_{j}) = (-1)^{q}Psi _{j-1}^{(2q)}(s_{j}), quad q=0,1.
Y(T) can be written as Y (T ) = Y T τ + ε g, where ε g is the error of the approximate solution compared to the true one.
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Alikhanov analyzed the error of the (L2-1_{sigma}) formula to approximate the Caputo fractional derivative, and got the following lemma.
To account for intrinsic variances [39] of the active and decoy structures, we bootstrapped the data sets and approximated the error of the awROC enrichments and awAUC.
The SI is based on the weak local truncation error of the approximate solution.
Also, the absolute error of the approximate solution is rapidly decreasing with m.
We obtain absolute error of the approximate solution values in the selected points ((x,t)=(frac{1}{2^i}, frac{1}{2^i})( i=1,2,ldots,6)).
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