Authentication with a one-dimensional CNN model using EEG-based brain-computer interface.

Brain-computer interface (BCI) technology uses electroencephalogram (EEG) signals to create a direct interaction between the human body and its surroundings. Motor imagery (MI) classification using EEG signals is an important application that can help a rehabilitated or motor-impaired stroke patient perform certain tasks. Robust classification of these signals is an important step toward making the use of EEG more practical in many applications and less dependent on trained professionals.

Robust control of series active power filters for power quality enhancement in distribution grids: Simulation and experimental validation.

This paper presents a simulation study and an experimental implementation of a single-phase Series Active Power Filter (SAPF) for the mitigation of harmonics in the load voltage. The aim is to regulate the injection voltage of the SAPF to compensate the grid voltage via the injection transformer in addition to maintaining the load voltage stable. The control strategies investigated in this work include Backstepping Sliding Mode Control (BSMC) and a neuro-fuzzy controller based on ANFIS (Adaptive Neuro-Fuzzy Inference System) l.