Computational fluid dynamics (CFD) has been used for several years to identify mechanical
risk factors associated with aneurysmal evolution and rupture as well as to understand flow …

Clustering techniques for functional data are reviewed. Four groups of clustering algorithms
for functional data are proposed. The first group consists of methods working directly on the …

Constructing generative models for functional observations is an important task in statistical
functional analysis. In general, functional data contains both phase (or x or horizontal) and …

In this paper we introduce a simple procedure to identify clusters of multivariate waveforms
based on a simultaneous assignation and alignment procedure. This approach is aimed at …

The problem of bi-clustering functional data, which has recently been addressed in
literature, is considered. A definition of ideal functional bi-cluster is given and a novel bi …

The use of distance measures in Statistics is of fundamental importance in solving practical
problems, such us hypothesis testing, independence contrast, goodness of fit tests …

This paper studies the problem of functional data clustering. Functional data have their own
characteristics and contain rich information that cannot be obtained when regarding the data …

In this paper we introduce a novel functional clustering method, the Bagging Voronoi K-
Medoid Aligment (BVKMA) algorithm, which simultaneously clusters and aligns spatially …

Constructing generative models for functional observations is an important task in statistical
function analysis. In general, functional data contains both phase (or x or horizontal) and …

Aims: This study monitored blood glucose profiles in normotolerant breastfeeding women,
with and without previous gestational diabetes, in real life in order to identify normal blood …