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Optimizing the Channel Selection and Classification Accuracy in EEG-Based BCI
TLDR
This paper proposes a novel sparse common spatial pattern (SCSP) algorithm for EEG channel selection that reduces the number of channels within a constraint of classification accuracy. Expand
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Optimizing Spatial Filters by Minimizing Within-Class Dissimilarities in Electroencephalogram-Based Brain–Computer Interface
TLDR
A major challenge in electroencephalogram (EEG)-based brain-computer interfaces (BCIs) is the inherent nonstationarities in the EEG data. Expand
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Weighted Transfer Learning for Improving Motor Imagery-Based Brain–Computer Interface
TLDR
We propose a novel transfer learning approach on the classification domain to reduce the calibration time without sacrificing the classification accuracy of MI-BCI. Expand
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Spatially sparsed Common Spatial Pattern to improve BCI performance
TLDR
This paper proposes a new Spatially Sparsed CSP (SS-CSP) algorithm by inducing sparsity in the spatial filters. Expand
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EEG Data Space Adaptation to Reduce Intersession Nonstationarity in Brain-Computer Interface
TLDR
A major challenge in EEG-based brain-computer interfaces (BCIs) is the intersession nonstationarity in the EEG data that often leads to deteriorated BCI performances. Expand
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Subject-to-subject adaptation to reduce calibration time in motor imagery-based brain-computer interface
TLDR
This paper proposes a subject-to-subject adaptation algorithm to reliably reduce the calibration time of a new subject to only 3-4 minutes. Expand
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Facilitating motor imagery-based brain–computer interface for stroke patients using passive movement
TLDR
The proposed FB-DSA algorithm linearly transforms the band-pass-filtered MI data such that the distribution difference between the MI and PM data is minimized. Expand
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Mutual information-based optimization of sparse spatio-spectral filters in brain–computer interface
TLDR
The proposed OSSSF algorithm combines a filter bank framework with sparse CSP filters to automatically select subject-specific discriminative frequency bands as well as to robustify against noise and artifacts. Expand
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Robust EEG channel selection across sessions in brain-computer interface involving stroke patients
TLDR
This paper investigates whether the selected channels from first session is also useful for subsequent sessions on other days for a stroke patient. Expand
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Spatio-Temporal Gaussian Process Models for Extended and Group Object Tracking With Irregular Shapes
TLDR
Extended object tracking has become an integral part of many autonomous systems during the last two decades. Expand
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