Sentence examples for norm errors from inspiring English sources

We will measure the accuracy of the proposed scheme using the maximum norm errors defined by e^{n}_{epsilon}=bigl| v^{n}-u^{n}bigr| _{infty}.

Fixing the spatial step (h=1/1text000) and taking different temporal steps, Table 1 presents the maximum (L_{2}) norm errors and convergence orders of our schemes; fixing the temporal step (tau =1/10text000) and taking different spatial steps, Table 2 presents the (L_{2}) norm errors and convergence orders in spatial direction.

The maximum norm errors between the exact and the numerical solutions are denoted by E_{infty}(h,tau)=max_{1leq nleq N} biglVert u^{n}-U^{n} bigrVert _{infty}.

In the test, we compute the maximum norm errors between the exact and the numerical solutions at the last time step by e(h,tau)=max_{1leq ileq N} biglvert u(x_{i},t_{M} -u_{i}^{M} -u_{i}rt, (11) where (u(x_{i},t_{M})) is the exact solution and (u_{i}^{M}) is the numerical solution with the mesh step sizes h and τ at the grid point ((x_{i},t_{M})).

FTH∞ estimator relies on a consistent fuzzy combination of two change detection tests; namely, likelihood ratio and averaged norm error.

By using the Nietzsche technique and Theorem 7, we easily obtain the following (L^{2}_{omega}) norm error estimates.

Taking the l1 norm error of 27 for example, the iteration times of our new algorithm is about 200.

The model results for thermal efficiency are within ± 5% for 59 of the 63 designs and have an L2 norm error of 3.0%.

The computed errors are defined by l 2  norm error:  E ( f ) = 1 n ∑ i = 1 n ( f ( x i ) − f r ( x i ) ) 2, (4.6).

Tables 1 and 2 present, respectively, the absolute error and the (L^2) norm error for (u x,t -{widetilde{u}}(x,t -{widetilde{u}nt values of q.

The temporal rate of convergence of (L_{2}) norm error as a function of the time step (Delta t) for (alpha = 1.75) is shown in Fig. 6.