Key Point Based Data Analysis Technique
ICIC '07 Proceedings of the 3rd International Conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence
A time-domain-constrained fuzzy clustering method and its application to signal analysis
Fuzzy Sets and Systems
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A new approach, designed for clustering data whose underlying distribution shapes are arbitrary, is presented. This study is concerned with the use of the skeleton of a cluster as its prototype, which can represent the cluster more closely than that of using a single data point. The given data set is then partitioned into those skeleton-represented clusters without any prior knowledge nor assumptions of hidden structures. A novel function called cluster characteristic function (CCF) has been constructed and the associated theorems have been proposed and proved that the proper number of clusters can be determined with the approach.