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Table 4 summarizes the number of multiplications at each iteration for different NSAF algorithms.
This means that comparing the complexity per iteration for different schemes is not fair unless the convergence speed is also taken into account.
The residual at the i th iteration is denoted as r i, and the curves of logarithmic scaled (dB) P FA versus P D at each iteration for different SNRs are shown in Figure 1.
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This part shows to be less predictable and presents some variation, which is mainly responsible for the small differences in required iterations for different scenarios.
The convergence of S-iteration for different classes of mappings in different spaces has been studied by many authors (see, e.g., [3, 4, 5, 17, 18, 20]).
Figure 8 PolSDE versus iterations for different initializations.
Next we examine the fastness of both iterations for different control conditions.
Table 6 shows the numbers of iterations for different values of ρ and various N.
Furthermore, for comparison, we show the number of iterations for different preconditioners with different regular parameters in Table 1.
Figure 3 Complexity of the SQP algorithm versus the number of iterations for different number of sub-blocks.
From this figure, we obtain Table 9 which illustrates the equivalent y iterations for different x values for identical error rate performances.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com