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The process of the combined method is also described.
Therefore, the SFrFT and DPCA combined method is elegant and effective in moving target identification.
Experiments show that the precision of the combined method is improved.
The simulation environment of the combined method is shown in Figure 6 and the BSS-only method in Figure 9.
The computation of the combined method is composed of three parts: beamforming filtering, separation filter estimation, and unmixing filtering.
It is proved in this paper that the combined method is strongly A-stable when θ∈[2/3,1.0].
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The proposed combined method was also used to evaluate the modal parameters of an experimental test on a structure containing closely spaced modes.
Only two of the Ffps (Ffp1 and Ffp3) and the combined method were able to predict all of the five targets, illustrating the usefulness of similarity fusion methods and combined data analysis.
The sensitivity and specificity of this combined method were 88.0 and 93.6%, respectively, and the positive and negative predictive values were 91.7 and 90.7%, respectively.
To observe the effect of multiple networks combined method was executed using sets of two (human yeast, human fly, fly yeast and human worm) as well as three (human yeast fly) networks.
If the signal is assumed to only be experiencing flat fading, the simplest combining method is to employ a selection combiner (SC).
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