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As the radius is shorten, when unknown samples are recognized, the probability that an uncertain sample is recognized as a certain sample is reduced.
The uncertain sample set, which contains most of the samples with linear inseparability, is classified by the SVM in the advanced recognition.
Additionally, samples with uncertain sample ID or poor DNA quality measured by negative result on real-time PCR for the porcine β-globin gene were excluded.
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By adjusting the sampling time, the uncertain sampled-data system can be stabilized.
Regarding the uncertain sampling problem encountered in real world applications, the sampling period designed for the controller is allowed to be variable within a given bound.
Stabilization of uncertain sampled-data strict-feedback systems is addressed.
In this paper, robust guaranteed cost control for uncertain sampled-data fuzzy systems is discussed.
Then, a design method of robust guaranteed cost state feedback controller for uncertain sampled-data fuzzy systems is proposed.
In this paper, as one of the design problems for NCSs, we consider optimal sampled-data control of linear systems with uncertain input delay and uncertain sampling period.
Third, CBQPL assigns the selected secondary uncertain samples with the same label as the most uncertain one, which is manually-labeled in AL within the same cluster.
The results that are obtained for the output-feedback controller are readily applied to the problem of robust sampled-data H∞ filtering with time-varying uncertain sampling rate.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com