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- W2353485281 abstract "A method is proposed to deal with the problem of blind classification of non-stationary transients, which usually occur in the field of signal processing and industrial control. There are two well-known shortcomings within K-Means algorithm prevailingly used in data clustering and other center-based clustering algorithms-the number of clusters must be known beforehand and the dependence of the algorithm performance on the initialization of the initial centers. By means of the method proposed here, above two problems can be solved as to improve the stability and classify the non-stationary transients. The wavelet coefficients of the transients are extracted to form the clustering sample space. The number of clusters is estimated through analyzing the gap statistics of clustering results, and then using harmonic means criterion to perform further classifying. Simulation result shows that the proposed method can be used to greatly reduce the misclassification probability." @default.
- W2353485281 created "2016-06-24" @default.
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- W2353485281 date "2004-01-01" @default.
- W2353485281 modified "2023-09-25" @default.
- W2353485281 title "Blind Signals Classification Based on Clustering Algorithms" @default.
- W2353485281 hasPublicationYear "2004" @default.
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