Sentence examples for signals classification from inspiring English sources

A lot of approaches for EEG signals classification have been developed [12].

This work investigates and explores whether the SRS combined with SFS give the best features for epileptic EEG signals classification.

While EEG feature extraction enables to characterize EEG signals, classification finds different categories in the input EEG signals.

M-PSK signals classification percentage is higher than 99% when SNR is not lower than 4 dB (considering 100 symbols).

The novelty that this paper introduces is the combination of GLCT and LBP applications to develop a new feature extraction algorithm applied to EMI signals classification.

The R-GDL machine-learning approach for full-body movements recognition is a novel method of time-varying multidimensional signals classification.

Multiple Signal Classification.

Step 2: LFM signal classification.

Fig. 4 General process of EEG signal classification.

And then the output detected signal is considered as a signal classification attribute.

The approach is based on the high-resolution technique known as multiple signal classification (MUSIC).