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References from A statistical mixture-of-experts framework for EMG artifact removal in EEG: empirical insights and a proof-of-concept application. Local targets link to admitted publications; unresolved targets remain external evidence.
Signal processing challenges for neural prostheses
10.1109/msp.2008.4408439 · 2007 · External reference
Evolving signal processing for brain-computer interfaces
2012 · External reference
Removal of EEG noise and artifact using blind source separation
10.1097/wnp.0b013e3180556926 · 2007 · External reference
Improving the interpretation of ictal scalp EEG: BSS–CCA algorithm for muscle artifact removal
10.1111/j.1528-1167.2007.01031.x · 2007 · External reference
FPGA implementation of EEG system-on-chip with automatic artifacts removal based on BSS-CCA method
2016 · External reference
BSS and ICA in neuroinformatics: from current practices to open challenges
10.1109/rbme.2008.2008244 · 2008 · External reference
Which BSS method separates better the EEG signals? A comparison of five different algorithms
10.1016/j.bspc.2021.103292 · 2022 · External reference
A dual-branch interactive fusion network to remove artifacts from single-channel EEG
10.1109/tim.2023.3342863 · 2023 · External reference
A GAN guided parallel CNN and transformer network for EEG denoising
10.1109/jbhi.2023.3277596 · 2023 · External reference
EEGDnet: fusing non-local and local self-similarity for EEG signal denoising with transformer
10.1016/j.compbiomed.2022.106248 · 2022 · External reference
EEGDiR: electroencephalogram denoising network for temporal information storage and global modeling through retentive network
10.1016/j.compbiomed.2024.108626 · 2024 · External reference
EEGdenoiseNet: a benchmark dataset for deep learning solutions of EEG denoising
10.1088/1741-2552/ac2bf8 · 2021 · External reference
A novel convolutional neural network model to remove muscle artifacts from EEG
2021 · External reference
Mixture of experts: a literature survey
10.1007/s10462-012-9338-y · 2014 · External reference
A survey on mixture of experts
10.36227/techrxiv.172055626.64129172/v1 · 2024 · External reference
EEG emotion recognition via identity based multi-gate mixture-of-experts network
2022 · External reference
A low-cost transhumeral prosthesis operated via an ML-assisted EEG-head gesture control system
10.1088/1741-2552/adae35 · 2025 · External reference
Mixture of experts for EEG-based seizure subtype classification
10.1109/tnsre.2023.3337802 · 2023 · External reference
An adaptive closed-loop ECoG decoder for long-term and stable bimanual control of an exoskeleton by a tetraplegic
10.1088/1741-2552/ac59a0 · 2022 · External reference
Methods for removing artifacts from EEG signals: a review
2024 · External reference
Targeted adversarial denoising autoencoders (TADA) for neural time series filtration
2025 · External reference
Twenty years of mixture of experts
10.1109/tnnls.2012.2200299 · 2012 · External reference
Deap: a database for emotion analysis; using physiological signals
10.1109/t-affc.2011.15 · 2011 · External reference
Building brain invaders: EEG data of an experimental validation
2019 · External reference
A large electroencephalographic motor imagery dataset for electroencephalographic brain computer interfaces
10.1038/sdata.2018.211 · 2018 · External reference
Enhanced μ rhythm extraction using blind source separation and wavelet transform
10.1109/tbme.2009.2021987 · 2009 · External reference
EMG contamination of EEG: spectral and topographical characteristics
10.1016/s1388-2457(03)00093-2 · 2003 · External reference
A survey on the feasibility of surface EMG in facial pacing
10.1109/embc.2016.7591040 · 2016 · External reference
A general dual-pathway network for EEG denoising
10.3389/fnins.2023.1258024 · 2024 · External reference
DHCT-GAN: improving EEG signal quality with a dual-branch hybrid CNN–transformer network
10.3390/s25010231 · 2025 · External reference
Measuring phase synchrony in brain signals
10.1002/(sici)1097-0193(1999)8:4<194::aid-hbm4>3.0.co;2-c · 1999 · External reference
Investigating critical frequency bands and channels for EEG-based emotion recognition with deep neural networks
10.1109/tamd.2015.2431497 · 2015 · External reference
