Sentence examples for trial corresponding to from inspiring English sources

Specifically, at the discrete time step k+1 (the onset of the trial corresponding to k=0), the effect associated with the i-th treatment sample at the preceding time step k, x i (k), is updated in the following manner: begin{array}{*{20}l} x_{i} k+1)=x_{i}(k) + w^{(t)}_{i} k+1) times expleft{-frac{k+1}{10}right}, end{array} (24).

In this approach, each trial (corresponding to an action video clip) was modeled as one event.

This resulted in a value for each trial, corresponding to the prestimulus activity in the right-lateralized fronto-parietal network.

The test was performed twice and the trial corresponding to the athletes' shortest time was further considered.

One severe hypoglycemic episode (2.1 mmol/l) occurred during the trial, corresponding to 0.03% of all measurements or 2.5% of.all patients.

This was a pilot study, designed to guide the planning for a large-scale trial corresponding to phase III of the Medical Research Council (MRC) guidelines on developing and evaluating complex interventions [ 25- 27].

The maximal height corresponded to the highest height before three consecutive unsuccessful trials corresponding to a 0.5 cm increase.

First, the test pair was selected after which the other 5 + 5 trials corresponding to the same target concepts were removed from the training set.

Because the meta-d' framework makes the assumption of a constant signal strength across trials, we computed metacognitive efficiency separately for easy and difficult trials (corresponding to 90 trials each) and averaged the two values, which were in turn averaged at the group level.

The results support the conclusion that single-trial detection can be achieved with an area under the ROC curve superior to 0.9 with less than ten sensors and 20 trials corresponding to the presentation of a target.

In the first analysis, only those trials corresponding to the presentation of a particular modality were used as input to the classifier and the task was to predict semantic category from EEG data.