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In data mining, k-means clustering is a method of cluster analysis which aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean. This results in a partitioning of the data space into Vo
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This documents explains in details with examples of the use Expectation Maximisation algorithm for maximum likelihood estimation in Gaussian mixtures.
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基于K均值的PSO聚类算法,窗函数法设计一个数字带通FIR滤波器，高斯白噪声的生成程序。- K-means clustering algorithm based on the PSO, A window function design FIR digital band-pass filter, Gaussian white noise generator.
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