Suqin Zhang

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In statistic and data mining, k-means is well known for its efficiency in clustering large data sets. The aim is to group data points into clusters such that similar items are lumped together in the same cluster. The K-means clustering algorithm is most commonly used algorithms for clustering analysis. The existing K-means algorithm is, inefficient while(More)
The method of optimal wavelet packet decomposition is proposed for rectal pressure signal feature extraction. By using wavelet packet algorithm, the mean wavelet coefficients and its corresponding energy component with high separability are selected as the feature vector according to the maximum separation degree of Fisher index, and the optimal features(More)
In this paper, we propose a multi-paradigm and multi-grain parallel execution model based on SMP-Cluster, which integrates coarse grain, mid grain and fine grain parallelism. Multiple paradigms supported by our model include task parallel, data parallel, sequential execution, data pipeline and task-farming paradigm. It can be achieved by extending the(More)