摘要模糊聚类分析算法能够通过目标函数准确地用公式表述聚类准则，从而较好地解决分类问题。

The clustering methods can exactly describe clustering criterion with formulations by the objective function. The classification problem can be better solved.

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本文对径向基函数网络提出了一种新的学习算法，利用最小均熵差准则对训练样本进行模式聚类。

This paper presents a new leaning method for radial basis function network, minimum mean entropy difference criterion algorithm is used to get pattern cluster of training sets.

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该算法不需标准化数据，应用一种基于统计直方图的全局准则函数进行聚类，特别适用于大规模数据。

This algorithm does not have to standardize the data, uses a kind of global criterion function based on the statistical histogram to depict clusters, specially is suitable for the large-scale data.

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