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Accordingly, we choose the correction cycle parameter M = 4 for all the subsequent simulations for our proposed method.
Moreover, in a correction cycle, the method designed in this paper only needs a single trajectory prediction, which reduces the on-board computation.
Moreover, without iteration, only a single trajectory prediction is required in a correction cycle, which is favorable for on-board calculation.
In each defect correction cycle, the solution is computed by non-linear multigrid iteration, in which collective symmetric Gauss-Seidel relaxation is used as the smoothing procedure.
Here, first-order discretization error accuracy is attained in a single multigrid cycle, and second-order accuracy in only one defect correction cycle.
From the figure, we see that the first-order algorithm takes one iteration step or one correction cycle (i = 1) to reach the steady-state value, while the second and fourth algorithms need two correction cycles (i = 2).
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From Figures 1,2 and3, the minimum required correction cycles ensuring convergence for carrier frequency offsets of 0.18, 0.48, and 0.6 are 2, 3, and 4, respectively, for the proposed method.
However, convergence to a point where the residual of the total error (the sum of the iteration error and the discretisation error) is of the order of the truncation error can be obtained in about seven defect correction cycles, according to estimates for the linear constant-coefficient equations.
The kAMP/ kVal-tRNA ratio (Table 1) indicates the amount of proofreading (the number of correction cycles per misacylated tRNA that evades editing).
Instead of the traditional design, code and test-cycles known from agile paradigms, we employ formal model, verification and correction-cycles.
Eddy current testing shows the potential for highly automated process monitoring that can reduce error correction and cycle time in AFP.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com