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An adaptive deep learning framework to classify unknown composite power quality event using known single power quality events
(Pergamon-Elsevier Science Ltd, 2021)
Distributed generation (DG) sources are preferred to meet today's energy needs effectively. The addition of many different types of renewable energy sources to the grid causes various problems in signal quality. Detection ...
A novel classification framework using multiple bandwidth method with optimized CNN for brain-computer interfaces with EEG-fNIRS signals
(Springer London Ltd, 2021)
The most effective way to communicate between the brain and electronic devices in the outside world is the brain-computer interface (BCI) systems. BCI systems use signals of being through neural activity in the brain to ...
A novel hybrid deep learning approach including combination of 1D power signals and 2D signal images for power quality disturbance classification
(Pergamon-Elsevier Science Ltd, 2021)
As a result of the widespread use of power electronic equipment and the increase in consumption, the importance of effective energy policies and the smart grid begins to increase. Nonlinear loads and other loads in electric ...