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We demonstrate the performance of the proposed method based on simulated and experimental data.
The experiments based on simulated and real environment prove the advantage of cognitive supervision.
RESULTS Experiments based on simulated and real data across different SNR levels and recording speeds show that our algorithms can accurately distinguish two fluorescence signals with ISI on the order of tens of milliseconds, shorter than the waveform's rise time.
The effectiveness of the proposed approach is investigated in "Numerical demonstration" by setting trades based on simulated and historical data, where the spread process exhibits a strong non-normal behaviour.
In the study, we conduct comparative evaluation of the performance between SWang and other tests, like T-test, F-test, SAM, and Fold-change, based on simulated and real microarray data.
We used the following procedure to test the methodologies presented above based on simulated and real data sets.
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The measuring principles of the two kinds of measuring devices are studied firstly, as well as the characteristics of their layouts and measurement uncertainties, based on simulating and actual measuring experiments.
Furthermore, a greedy heuristic and a fix-and-optimize heuristic based on simulated annealing and exact methods (Branch & Bound and cutting methods) are proposed to solve the model.
Given only one dataset is based on simulated data and the other two are real datasets in which the authors adjusted for multiple testing using different methods we felt adjusting further confounded the comparisons and thus simply present the rank unadjusted values for scrutiny.
The formulation provides the basis for a stochastic optimization procedure based on simulated annealing and also for visualisation and user interaction through a graphical interface.
This independent validation of the design is based on simulated annealing and restrained molecular dynamics simulation in vacuo, comparable to procedures used to refine NMR and X-ray structures.
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