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where, as in Eq. 1, indexes 1 and 2 refer to the two sub-models computed from the two ASM-V sub-data sets, and index 0 refers to the original ASM-V candidate model.
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(The photograph is in the Page 1 index).
Step 1: Index building.
Fig. 1 Index map.
P 1: index.html.html
1) Index parameters and sets.
Starting from W 1, we then search 2K−1 indexes nearest W 1 to form a circle cluster.
On the basis of W 2 and the EMV features, K−1 indexes nearest to W 2 in the circle cluster are searched.
Based on the EMV features that the significant amplitudes gather in a circle cluster, the MFB-CoSaMP first locates the index of maximal amplitude in u in the W 1 identification and then search the 2K−1 indexes nearest to it.
According to the W 1, we then locate the other 2K−1 indexes to form support-set W 1. In CoSaMP, the signal components that carry a lot of energy locate in the identification process whereas the EMV features indicate that the significant amplitudes only gather in one circle cluster.
35 indexes were kept.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com