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A new strategy of feature classification method for speaker recognition based on the grid-density clustering is presented. According to the concept of density-based and grid-distance-based distribution in the Mel-frequency cepstrum domain, the feature vectors of each speaker were self-adaptively classified into L clusters with less overlapped. With these convex and non-interwoven clusters, the Gaussian...
In this paper, we propose a clustering linear discriminant analysis algorithm (CLDA) to accurately decode hand movement directions from a small number of training trials for magnetoencephalography-based brain computer interfaces (BCIs). CLDA first applies a spectral clustering algorithm to automatically partition the BCI features into several groups where the within-group correlation is maximized...
In wireless sensor networks, the accuracy of data fusion is likely to be contaminated by the environment affects nearby the nodes. In this paper, an appropriate fusion model and algorithm is given to solve this problem. According to the clustering fusion model, a weighted fuzzy fusion algorithm based on fuzzy reasoning for cluster heads, is proposed. The advantage of this algorithm is to vary weight...
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