After F a s t [6] introduced the theory of statistical convergence of a real sequence, it has become popular among mathematicians ([2], [7]–[9], [17]). The ideas of statistical limit superior and limit inferior were first extensively studied by F r i d y and O r h a n [9]. After K o s t y r k o et al. [10] extended the idea of statistical convergence to I-convergence using the concept of an ide...

With the aid of regular integral operators, we will be able to generalize statistical limit-cluster points and limit inferior-superior ideas on time scales in this work. These two topics, which have previously been researched separately from one another sometimes only discrete case other times continuous case, studied at a single study. We investigate relations these concepts with each come num...

In the preceding paper [ l ] 2 Buck defines a class of "subsequences" of a multiple sequence and shows that "almost all" of such subsequences have certain properties. This note is essentially based on a different choice of the definition of "subsequences" ; that is, this paper and [ l ] are generalizations in different directions of a preceding paper by Buck and Pollard (reference 2 of [l ]). I...

Abstract In this paper, a multi-sphere support vector clustering algorithm (SHMSVC) is proposed, which is based on statistical histogram, suitable for large data set, robust to noise and outliers, and able to automatically determine the number of clusters, and identify data points with arbitrary contours of cluster boundaries. The proposed SHMSVC algorithm consists of two major phases. In the f...

Clustering plays an outstanding role in data mining research. Among the various algorithms for clustering, most of the researchers used the Fuzzy C-Means algorithm (FCM) in the areas like computational geometry, data compression and vector quantization, pattern recognition and pattern classification. In this research, a simple and efficient implementation of FCM clustering algorithm is presente...

We present a new statistical approach, called principal clusters analysis, for analyzing millions of user navigations among Web documents. This technique can identify distinct clusters of related information on a given topic. In addition, it can determine which information items within a cluster are useful starting points to explore the topic of the cluster, as well as key documents within the ...

In this paper we investigate the notion of I-statistical ϕ-convergence and introduce IS-ϕ limit points cluster real number sequence also studied some its basic properties.

make for the interpretations of findings and the implications thereof for educational practice and future research. A new section of Perspectives on Medical Education, entitled Statistical points and pitfalls, directly tackles these analytical issues. The overall purpose of this series is to help readers and researchers alike increase awareness of how to use statistics, why and how we fall into...

This paper describes how to cluster together the phrases of a phrase-based statistical machine translation (SMT) system, using information in the phrase table itself. The clustering is symmetric and recursive: it is applied both to sourcelanguage and target-language phrases, and the clustering in one language helps determine the clustering in the other. The phrase clusters have many possible us...