In this respect, two different metabolomics concepts can be distinguished: targeted and non-targeted.
The new system is able to distinguish targets, such as certain types of electronic circuits that may be used in explosive or espionage devices, including items such as pipes, drinks cans and nails, that may be mistaken for a genuine target by traditional radar and metal detectors.
Time frequency analysis methods were applied to the obtained datasets to show that m-D signatures can be exploited to distinguish targets with micro-motions from stationary targets.
As a consequence application-relevant issues such as shelf life and robust protocols distinguishing targets from false responses have received very little attention.
Unless d' is very large, the two distributions overlap to some degree, which means that no signal strength perfectly distinguishes targets from foils.
Although the geometric distortion is corrected, it is also difficult to distinguish targets in cross-range direction in Figure 10d since θ r is around 0 ∘.
It is the inevitable drawback of side-look SAR to distinguish targets at the forward and backward directions [1]. Figure 10 Simulation results of subimage formation and geometric-distortion correction.
These findings suggest that non-blinkers are more efficient in distinguishing targets from distractors at a relatively early processing stage.
Given the findings from Experiment 1 and 2, we predict that when category information does not distinguish targets from distractors, non-blinkers are forced to process each stimulus much more elaborately, rendering an efficient selection of targets difficult or impossible.
Given these as well as previous findings [20], [24], we predicted that non-blinkers should only show reduced distractor-related ERP activity (compared to that of blinkers) when alphanumeric category information is present, allowing them to efficiently distinguish targets from distractors.
(3) A procedure based on recursive-feature-elimination is able to uncover from the large initial data sets those features that best distinguish targets for any TF, providing clues relevant to its biology.
