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The peak identification was tested using the RI (retention time index) method.
Experimentally, the spatial damping identification was tested against: modal and spatial incompleteness, differences in viscous and hysteretic damping models, the performance of identification methods and the effect of damping treatments.
The proposed design for the threshold identification was tested at different SNR levels in ordtr to determine the behaviour of the algorithm in different operating conditions.
The performance of TD-GF on proteoform identification was tested on an Escherichia coli (EC) data set.
For each of the five sets of stimuli conveying the five traits, accuracy of identification was tested with separate ANOVAs (trait × intensity bin).
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The proposed optimal regulatory control law incorporating system identification is tested experimentally by regulation of culture glucose concentration at different setpoint conditions.
In order to investigate the efficiency of the proposed method, several examples in system identification are tested to validate that the proposed method can outperform some state-of-the-art methods.
Gene regions with variability that enabled specific positive identification were tested on additional species within each genus to further test the region's ability to provide identification at the species level.
Single anatomical brain regions that consistently identified object exemplars or categories across participants were selected using cross-validation, and the significance of those identifications was tested across participants.
The stability of the identification algorithm was tested on virtual tensile tests performed on the same sample type by adding perturbations to numerical simulation results.
The identification method was tested for a wide range of conditions, and proved suitably robust to changes in system configuration, noisy data and modelling error.
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