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Hybrid Brain-Computer Interfaces (BCI) has shown great promise for neuro-prosthetics and assistive devices in the field of rehabilitation. However, the complexity involved with the system design and time cost for classification of motor tasks is a core problem when we step into clinical applications. To help address this problem, simultaneous measurements of Electroencephalography (EEG) and functional...
Association rule discovery from sensor time series is a challenge. Because the time series has high dimensional, numerical and continuous nature. However the general association methods can only deal with data which are symbolic and discrete. And the general association methods have high processing time consumption when the data have high dimension. So a useful framework is proposed, which is pre-processing,...
In unconstrained scenes, the change of expression and pose may lead to mismatching of the human face and ear images, and the recognition rate may also decrease. A method fusing depth and texture information is proposed to deal with the problem. We employ different recognition strategies based on the different characteristics of the spherical depth map and the spherical texture map. The learning to...
Non line of sight (NLOS) error identification and mitigation is of great importance in ultra wideband (UWB) ranging and localization. Based on the features extracted from the received waveform in practical experiments, a machine learning method is proposed for UWB NLOS identification in this paper. Corresponding NLOS error mitigation method is also given based on the identification results. Compared...
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