Efendi N. Nasibov

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Among various types of clustering methods, partition-based methods such as k-means and FCM are widely used in the analysis of such data. However, when duration between stimuli is different, such methods are not able to provide satisfactory results because they find equal size clusters according to the fundamental running principle of these methods. In such(More)
The difference of Fuzzy Joint Points (FJP) algorithm from other neighborhood-based clustering algorithms is that it uses the concept of fuzzy neighborhood when computing the neighborhood relations. Among the proposed methods, none of them is perfect for all aspects of clustering requirements. Although FJP algorithm has superiority by its advantages of(More)