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Based on this filtering analysis, we conclude that none of the candidates from the initial lists can pass all of the filters.
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Based on this filter, Authors [5] introduce a general smoothing procedure with a single parameter to control smoothing degree.
Based on this filter property, which can be described by the panel parameters, a method of computing the acoustic pressure wave distribution in the duct is presented.
Based on this filter bank of CDUKF, a novel online OED design procedure is developed, that is used to identify the correct parameter set out of several available sets for measured blood glucose concentrations.
Based on this filter and the approximation property of radial basis function (RBF) neural networks, an adaptive neural output-feedback controller is designed via backstepping technique, which can guarantee that all the signals in the closed-loop system are ultimately bounded.
All analyses reported below are based on this filtered dataset.
Based on this filter, we discarded 132 loci, primarily due to multibanded phenotypes.
Based on this filtered network, we study several potentially interesting interactions and subgraphs.
Based on this filter, the number of selected targets was drastically reduced to a final set of 31 targets.
Based on this assumption, filtering methods can be tested using independently recorded human ECG and CPR artifacts, added at different signal-to-noise ratios (SNRs) according to (1) s cor = s ecg + α SNR · s cpr, with α SNR = P ecg P cpr · 1 0 SNR / 10.
A linear matrix inequality (LMI) condition is obtained for the existence of admissible filters, and based on this, the filter design is cast into a convex optimization problem, which can be readily solved via standard numerical software.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com