Devi, B. Bharathi and Sarma, VVS (1984) A fuzzy multistage evolutionary (FUME) clustering technique. In: Pattern Recognition Letters, 2 (3). pp. 139-145.
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n this paper, a multistage evolutionary scheme is proposed for clustering in a large data base, like speech data. This is achieved by clustering a small subset of the entire sample set in each stage and treating the cluster centroids so obtained as samples, together with another subset of samples not considered previously, as input data to the next stage. This is continued till the whole sample set is exhausted. The clustering is accomplished by constructing a fuzzy similarity matrix and using the fuzzy techniques proposed here. The technique is illustrated by an efficient scheme for voiced-unvoiced-silence classification of speech.
|Item Type:||Journal Article|
|Additional Information:||Copyright of this article belongs to Elsevier Science.|
|Keywords:||Multistage clustering; fuzzy clustering; N-Purlieus relation; Min-max clustering; VUS classification.|
|Department/Centre:||Division of Electrical Sciences > Computer Science & Automation (Formerly, School of Automation)|
|Date Deposited:||22 Jul 2009 10:54|
|Last Modified:||19 Sep 2010 05:32|
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