Results 161 to 170 of about 5,816 (193)
Modified electrolytic manganese dioxide (MEMD) for oxygen generation in alkaline medium
Journal of Solid State Electrochemistry, 2015 Undoubtedly, hydrogen will play an important role in the energy sector in the near future, in particular, as a fuel for transportation. However, electrolytic hydrogen generation is energy intensive and the means to save energy have been widely studied, as for example, the use of proton exchange membranes to minimize the voltage drop across the ...
Delgado, D. +3 more
openaire +2 more sources
Some of the next articles are maybe not open access.
Related searches:
Related searches:
Ocular and muscle artifacts suppression from EEG through MEMD and statistics
Multimedia Tools and Applications, 2023Voruchu Sai Babu, Avinash S. Vaidya
exaly +2 more sources
Biomedizinische Technik, 2018 EEG source localization is determining possible cortical sources of brain activities with scalp EEG. Generally, every step of the data processing sequence affects the accuracy of EEG source localization.
Kheng Seang Lim +2 more
exaly +2 more sources
Automatic Artifact Reduction Based on MEMD- for Seizure Prediction
2018 IEEE Biomedical Circuits and Systems Conference (BioCAS), 2018The performance of seizure prediction is usually affected by various kinds of artifacts, especially by physiological artifacts. To improve the performance of seizure prediction, this paper proposed an automatic artifact reduction method based on multivariate empirical mode decomposition and independent component analysis (MEMD-ICA). The proposed method
Lihan Tang +3 more
openaire +2 more sources
Hand Movement Prediction Based on EEG signals by Combining MEMD and CSP
2020 2nd International Conference on Image Processing and Machine Vision, 2020For prosthetic limb control and rehabilitation training of disabilities, it is important to use electroencephalography (EEG) to recognize different hand movements to assist the disabilities. In this paper, we proposed a novel method by combining multivariate empirical mode decomposition (MEMD) and common spatial pattern (CSP) to extract EEG features ...
Yi Tao, Nong Yan, Gang Wang 0005
openaire +1 more source
ROCOF Estimation via EMD, MEMD and NA-MEMD
2019This paper presents results of the rate of change of frequency (ROCOF) estimation using Huang’s Empirical Mode Decomposition (EMD), Multivariate Empirical Mode Decomposition (MEMD) and Noise-Assisted Multivariate Empirical Mode Decomposition (NA-MEMD).
Maja Muftić Dedović +3 more
openaire +1 more source
Research on improved information fusion of accelerometers based on MEMD technology
Proceedings of the 2016 International Conference on Intelligent Information Processing, 2016Accelerometer can measure signal of multiple channels simultaneously, but it has in coupling problems in multi-channel signal. In this paper, an improved method based on the multivariate empirical mode de-composition (MEMD) combined with holo-spectrum technology is put forward.
Yuan Shen, Dongcai Liu
openaire +2 more sources
EEG energy analysis for evaluating consciousness level using dynamic MEMD
2014 International Joint Conference on Neural Networks (IJCNN), 2014Analysis of electroencephalography (EEG) energy is a useful technique in the brain signal processing. In this paper, we present a novel data analysis method based on a dynamic multivariate empirical mode decomposition (D-MEMD) algorithm to analyze EEG energy of three different conscious states such as normal awake, comatose and brain death.
Gaochao Cui +3 more
openaire +2 more sources
Comparison of EMD, MEMD and 2T-EMD by analyzing standard artificial signals and EEG
2017 International Joint Conference on Neural Networks (IJCNN), 2017EEG (electroencephalography) can be analyzed quantitatively by introducing the EEG energy index in EEG preliminary examination of determination of brain death. EMD (empirical mode decomposition), MEMD (multivariate empirical mode decomposition), and 2T-EMD (turning tangent empirical mode decomposition) can be used to analyze coma and quasi-brain-death ...
Yao Miao, Jianting Cao
openaire +2 more sources
A MEMD Method of Human Emotion Recognition Based on Valence-Arousal Model
2017 9th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC), 2017Since emotions play an important role in human-machine interaction and EEG based emotion recognition is a challenging study due to nonstationary behavior of the signals, sophisticated signal processing methods are required to extract the hidden patterns in the EEG.
Yue He, Qingsong Ai, Kun Chen
openaire +1 more source