Results 21 to 30 of about 1,394,604 (278)

RF Channel-Selectivity Sensing by a Small Antenna of Metamaterial Channel Filters for 5G Sub-6-GHz Bands

Sensors, 2020
In this paper, a new small antenna is suggested for 5G Sub-6-GHz band mobile communication. It can change the channel among the three given bands (called the 3.5-GHz area), as a wide-band antenna is connected to a small multiplexer comprising three ...
Muhammad Kamran Khattak, Changhyeong Lee, Heejun Park, Sungtek Kahng   +3 more
doaj   +1 more source

Mental Stress Classification Based on Selected Electroencephalography Channels Using Correlation Coefficient of Hjorth Parameters

Brain Sciences, 2023
Electroencephalography (EEG) signals offer invaluable insights into diverse activities of the human brain, including the intricate physiological and psychological responses associated with mental stress.
Ala Hag, Fares Al-Shargie, Dini Handayani, Houshyar Asadi   +3 more
doaj   +1 more source

Emotion Classification from Multi-Band Electroencephalogram Data Using Dynamic Simplifying Graph Convolutional Network and Channel Style Recalibration Module

Sensors, 2023
Because of its ability to objectively reflect people’s emotional states, electroencephalogram (EEG) has been attracting increasing research attention for emotion classification.
Xiaoliang Zhu, Gendong Liu, Liang Zhao, Wenting Rong, Junyi Sun, Ran Liu   +5 more
doaj   +1 more source

A Transform-Based Feature Extraction Approach for Motor Imagery Tasks Classification

IEEE Journal of Translational Engineering in Health and Medicine, 2015
In this paper, we present a new motor imagery classification method in the context of electroencephalography (EEG)-based brain-computer interface (BCI).
Hamza Baali, Aida Khorshidtalab, Mostefa Mesbah, Momoh J. E. Salami   +3 more
doaj   +1 more source

A Survey on EEG-Based Solutions for Emotion Recognition With a Low Number of Channels

IEEE Access, 2022
The market uptake of Brain-Computer Interface technologies for clinical and non-clinical applications is attracting the scientific world towards the development of daily-life wearable systems.
Andrea Apicella, Pasquale Arpaia, Francesco Isgro, Giovanna Mastrati, Nicola Moccaldi   +4 more
doaj   +1 more source

A Fast, Open EEG Classification Framework Based on Feature Compression and Channel Ranking

Frontiers in Neuroscience, 2018
Superior feature extraction, channel selection and classification methods are essential for designing electroencephalography (EEG) classification frameworks.
Jiuqi Han, Yuwei Zhao, Hongji Sun, Jiayun Chen, Jiayun Chen, Ang Ke, Ang Ke, Gesen Xu, Hualiang Zhang, Jin Zhou, Changyong Wang   +10 more
doaj   +1 more source

Exploring UAV's multi-domain joint anti-jamming intelligent decision algorithm

Xibei Gongye Daxue Xuebao, 2021
To understand the complex communication environment of a UAV in battlefield, its unknown channel statistics information and poor intelligent jamming and anti-jamming capability, the multi-domain anti-jamming problem is studied, and a multi-domain joint ...

doaj   +1 more source

Intelligent Anti-Jamming Communication for Wireless Sensor Networks: A Multi-Agent Reinforcement Learning Approach

IEEE Open Journal of the Communications Society, 2021
In this article, we investigate intelligent anti-jamming communication method for wireless sensor networks. The stochastic game framework is introduced to model and analyze the multi-user anti-jamming problem, and a joint multi-agent anti-jamming ...
Quan Zhou, Yonggui Li, Yingtao Niu
doaj   +1 more source

Decoding finger movements from ECoG signals using switching linear models

Frontiers in Neuroscience, 2012
One of the most interesting challenges in ECoG-based Brain-Machine Interface is movement prediction. Being able to perform such a prediction paves the way to high-degree precision command for a machine such as a robotic arm or robotic hands.
Remi eFlamary, Alain eRakotomamonjy
doaj   +1 more source

Optimal Channels and Features Selection Based ADHD Detection From EEG Signal Using Statistical and Machine Learning Techniques

IEEE Access, 2023
Attention deficit hyperactivity disorder (ADHD) is one of the major psychiatric and neurodevelopment disorders worldwide. Electroencephalography (EEG) signal-based approach is very important for the early detection and classification of children with ...
Md. Maniruzzaman, Md. Al Mehedi Hasan, Nobuyoshi Asai, Jungpil Shin   +3 more
doaj   +1 more source