Regularizing common spatial patterns to improve BCI designs: unified theory and new algorithms.
about
A neural network-based optimal spatial filter design method for motor imagery classificationReview of the BCI Competition IV.Decoding continuous limb movements from high-density epidural electrode arrays using custom spatial filtersPreparing Laboratory and Real-World EEG Data for Large-Scale Analysis: A Containerized Approach.Brain-to-brain entrainment: EEG interbrain synchronization while speaking and listening.Z-score linear discriminant analysis for EEG based brain-computer interfaces.The advantages of the surface Laplacian in brain-computer interface research.The synergy between complex channel-specific FIR filter and spatial filter for single-trial EEG classificationAn evidence-based combining classifier for brain signal analysisPredicting BCI subject performance using probabilistic spatio-temporal filters.Probabilistic Common Spatial Patterns for Multichannel EEG Analysis.Decoding covert shifts of attention induced by ambiguous visuospatial cuesHybrid EEG-fNIRS Asynchronous Brain-Computer Interface for Multiple Motor Tasks.Decoding human swallowing via electroencephalography: a state-of-the-art review.Critical issues in state-of-the-art brain-computer interface signal processing.Comparing Features for Classification of MEG Responses to Motor Imagery.Combining multiple features for error detection and its application in brain-computer interface.Adaptive Laplacian filtering for sensorimotor rhythm-based brain-computer interfacesL1 norm based common spatial patterns decomposition for scalp EEG BCIA Novel Fixed Low-Rank Constrained EEG Spatial Filter Estimation with Application to Movie-Induced Emotion Recognition.Three-Class EEG-Based Motor Imagery Classification Using Phase-Space Reconstruction Technique.EEG feature comparison and classification of simple and compound limb motor imageryLocal temporal correlation common spatial patterns for single trial EEG classification during motor imagery.Scale-Dependent Signal Identification in Low-Dimensional Subspace: Motor Imagery Task Classification.Regularized Linear Discriminant Analysis of EEG Features in Dementia Patients.Evolutionary Algorithm Based Feature Optimization for Multi-Channel EEG Classification.How to Build a Hybrid Neurofeedback Platform Combining EEG and fMRI.Deep learning with convolutional neural networks for EEG decoding and visualizationRelevant Feature Integration and Extraction for Single-Trial Motor Imagery Classification.Blind Source Separation for Unimodal and Multimodal Brain Networks: A Unifying Framework for Subspace Modeling.Robust Averaging of Covariances for EEG Recordings Classification in Motor Imagery Brain-Computer Interfaces.Regularized common spatial patterns with subject-to-subject transfer of EEG signals.Predicting Inter-session Performance of SMR-Based Brain-Computer Interface Using the Spectral Entropy of Resting-State EEG.Sparse Bayesian Learning for Obtaining Sparsity of EEG Frequency Bands Based Feature Vectors in Motor Imagery Classification.Uncorrelated multiway discriminant analysis for motor imagery EEG classification.Decoding three-dimensional reaching movements using electrocorticographic signals in humans.Motor Imagery Impairment in Postacute Stroke PatientsBrain-Computer Interface for Control of Wheelchair Using Fuzzy Neural Networks.Common spatio-time-frequency patterns for motor imagery-based brain machine interfaces.Robust common spatial filters with a max-min approach.
P2860
Q27308802-F552405B-3FF9-4E15-B5D9-24C865FE2ADAQ28727178-E03C03DF-0A61-41DB-B8EE-C6FF098EA78DQ30543179-DFE1346B-783D-4E84-9673-11FA8D0AD4C9Q31063216-4B384927-8831-48CD-AE4B-60093B5F8DFDQ33829998-FC97C956-2B94-4253-AC09-1C963017346FQ34994683-1E69B4C5-9319-466F-937C-AF28718812FFQ35034495-B4D710C3-2F44-4E93-B61F-122F41624786Q35034888-0341A41B-E604-4F03-9B14-0C7CF65DB1ADQ35083371-1205FA01-BFC2-4A1A-A3DD-A968F3D0A1EBQ35097242-4B32D8BF-13A8-4BC0-8F0B-EBDF6ABBF63CQ35636473-D682FA33-44D3-4EDF-A6AB-0A3B40EC07CDQ35753347-4A361CA8-A9B9-4DDA-94BC-70E5A0D7D3F7Q35884987-67178E3F-288D-4C63-A609-8BDE47FF103DQ36130546-185BD1ED-16A5-4318-BCF3-566D4B12626EQ36141182-A694F62F-CC9D-4ACE-8981-BF1DF25C0AB5Q36228532-8A6AF894-61B6-4819-9242-E7A4F9779CF2Q36549747-C300EABF-B601-4127-8C07-8A2A0B8EC825Q36698864-CE4FCE92-7544-4191-98C4-B165BB6891B1Q37113649-AE75A3D6-A979-4CDD-9274-F944C8E7C505Q37202110-E4C16154-31E1-4D23-8497-6B4C326A228DQ37290763-99A53172-CABD-4E84-8DCA-E27DEFFF5DB8Q37368058-4E0643BF-713A-4740-8F65-3B3A5915988DQ37368522-FCFA5F9B-7BCE-4C74-ACFD-B95170E16699Q37418895-B36261A0-DC1B-41C6-B2DD-C3DB2B97BAE9Q37452576-03B6B3EF-CFB8-4987-A8F9-8DEB6AE16770Q37617432-49D9C1A1-009A-4F3B-A907-A0CB761BC9F4Q37712572-95AC10C4-3DE0-45B3-8EC7-CDCD3F8C7782Q38637379-DA6EB94B-ABBE-4713-A88E-72AAFB916B76Q38679930-022A81C7-12CE-4F48-95ED-2A2B02785ED1Q38810078-F7AF7DFA-BA66-4DE5-9E2C-970E72BAE048Q38836887-E634E30D-8234-4F99-82E1-0EC6FB1CFC26Q38872411-46A9FB51-B633-45B5-9FF9-BA3EA732B94BQ39027622-28E8FD9D-1053-4E2C-B96C-CAFF2BE370ADQ39632676-07969078-F9AC-44A2-97C5-131AA21B8A01Q40926590-8623B781-F28F-4898-AF93-5225C9A66DA2Q41180613-058C0A02-8BF1-42F6-A125-657D1FCBE908Q41848686-D43A0EA9-583B-4E78-8C43-097636EEF33FQ42383758-74BF439C-C41A-4750-B90C-00E956C87599Q42874630-CE571742-CAB3-4ADD-B6BA-490A0952FB34Q45397391-8D2D2F78-D685-4A1A-A79F-3DF834DCD005
P2860
Regularizing common spatial patterns to improve BCI designs: unified theory and new algorithms.
description
article científic
@ca
article scientifique
@fr
articolo scientifico
@it
artigo científico
@pt
bilimsel makale
@tr
scientific article published on 30 September 2010
@en
vedecký článok
@sk
vetenskaplig artikel
@sv
videnskabelig artikel
@da
vědecký článek
@cs
name
Regularizing common spatial pa ...... ied theory and new algorithms.
@en
Regularizing common spatial pa ...... ied theory and new algorithms.
@nl
type
label
Regularizing common spatial pa ...... ied theory and new algorithms.
@en
Regularizing common spatial pa ...... ied theory and new algorithms.
@nl
prefLabel
Regularizing common spatial pa ...... ied theory and new algorithms.
@en
Regularizing common spatial pa ...... ied theory and new algorithms.
@nl
P1476
Regularizing common spatial pa ...... ied theory and new algorithms.
@en
P304
P356
10.1109/TBME.2010.2082539
P577
2010-09-30T00:00:00Z