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Extensive studies have been done on the ECCM to combat deceptive jamming, such as pulse diversity [9 11], motion features discrimination [12], and data fusion-based methods [13 15].
For example, as a classical statistical hypothesis test method, t-test has been adopted to select features in the form of bagged t-test [ 33] and modified τ-statistics [ 34] in research areas such as genotype data classification [ 35] and hippocampal shape features discrimination [ 36].
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The identification network could enhance the feature discrimination for person re-identification.
The radio broadcast database and the BNSI broadcast news database were used for feature discrimination and segmentation ability evaluation.
In general, the EFS framework can be used in any such tasks in which it is applicable to take advantage of enhanced feature discrimination.
Thus, in order to improve not only the feature discrimination in the feature space, but also the audio retrieval performance, next we propose applying a similar methodology that is utilized in feed-forward ANNs.
A method for transforming and modifying traditional audio features by an evolutionary optimization algorithm is proposed, one that improves feature discrimination as well as audio classification and retrieval performance.
Importantly, this model can explain this type of feature discrimination without the need for relative motion cues.
Whisker tip diameters are thus somewhat smaller or comparable to the known limits of surface feature discrimination in rats.
If, however, the feature discrimination performance is changing over time like in subject zp, this bias update might not be sufficient any more.
For example, in a feature discrimination task using color and form as cues, larger positivity was demonstrated in the P3 time window for target stimuli, but only when attention was directed to stimulus color [29].
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