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There has been an increasing attention on Electroencephalograph (EEG) based personal identification over the last decade. Most existing methods address this problem by Euclidean metric based Nearest Neighbor (NN) search. However, under various recording conditions, simple Euclidean distance cannot model the similarity relations between EEG signals precisely. To overcome this drawback, a local metric...
Traditional hyperspectral classification methods based on per-pixel spectral or texture features fail to take account of spatial structure and spatial correlation characteristics. In order to overcome this problem, a mixed classification method is proposed which incorporates spatial information by fusion of object-based segmentation with pixel-wise classifier. This paper tentatively assesses two mixed...
In this paper, we mainly propose an incremental version of improved least squares twin support vector machine (IILSTSVM), based on inverse matrix-free method. This algorithm can meet the requirement of online learning to update the existing model. In the case of low dimension data, this method effectively improves training speed of incremental learning. According to updating inverse matrix, we can...
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