Let x1,⋯,xn be independent observations of size p, each them belonging to one c distinct classes. We assume that within the class a are characterized by their distribution N(0,1 pCa) where here C1,⋯,Cc some non-negative definite p×p matrices. This paper studies asymptotic behavior symmetric matrix Φ˜kl=p(x kTx l)2δ k≠l when p and n grow infinity with p→c0. Particularly, we prove that, if covari...

Functional data clustering is to identify heterogeneous morphological patterns in the continuous functions underlying discrete measurements/observations. Application of functional has appeared many publications across various fields sciences, including but not limited biology, (bio)chemistry, engineering, environmental science, medical psychology, social and so on. The phenomenal growth applica...

In this paper we propose a novel clustering method for functional data based on the principal curve approach. By are approximated using component analysis (FPCA) and is then performed scores. The proposed makes use of nonparametric curves to summarize features scores extracted from original data, probabilistic model combined with Bayesian Information Criterion employed automatically simultaneou...

Spectral techniques are often used to partition the set of vertices a graph, or form clusters. They based on Laplacian matrix. These allow easily integrate weights edges. In this work, we introduce p-Laplacian, generalized matrix with potential, which also allows us take into account vertices. vertex independent edge weights. way, can cluster importance vertices, assigning more weight some than...

this paper compares clusters of aligned persian and english texts obtained from k-means method. text clustering has many applications in various fields of natural language processing. so far, much english documents clustering research has been accomplished. now this question arises, are the results of them extendable to other languages? since the goal of document clustering is grouping of docum...