Motivation: Estimating a covariance matrix from high dimensional data using a small number of samples is known to be statistically challenging, and yet it is a problem that arises frequently in practice. For some kinds of data, it is reasonable to assume that the variables can be clustered or grouped into types that share similar connectivity or correlation patterns. For example, genes can be g...

In thispaper a reviewof type-2 fuzzy logic applications inpattern recognition, classificationandclustering problems is presented. Recently, type-2 fuzzy logic has gained popularity in a wide range of applications due to its ability tohandle higher degrees of uncertainty. In particular, therehavebeen recent applications of type-2 fuzzy logic in the fields of pattern recognition, classification a...

In this work a new set of clustering criteria for the structuralization of universes in the logical combinatory approach of the Pattern Recognition Theory is introduced. The criteria are considered for classical partitions and covers as well as fuzzy classes. The existing relationships between these criteria are studied. An example of an application of the criteria introduced herein is also inc...

A generalized prototype-based classi2cation scheme founded on hierarchical clustering is proposed. The basic idea is to obtain a condensed 1-NN classi2cation rule by merging the two same-class nearest clusters, provided that the set of cluster representatives correctly classi2es all the original points. Apart from the quality of the obtained sets and its 5exibility which comes from the fact tha...

Texture analysis and classification are some of the problems which have been paid much attention by image processing scientists since late 80s. If texture analysis is done accurately, it can be used in many cases such as object tracking, visual pattern recognition, and face recognition. Since now, so many methods are offered to solve this problem. Against their technical differences, all of the...

Earthquakes arrive without previous warning and can destroy a whole city in a few seconds, causing numerous deaths and economical losses. Nowadays, a great effort is being made to develop techniques that forecast these unpredictable natural disasters in order to take precautionary measures. In this paper, clustering techniques are used to obtain patterns which model the behavior of seismic temp...

Clustering for the analysis of the genes organizes the patterns into groups by the similarity of the dataset and has been used for identifying the functions of the genes in the cluster and analyzing the functions of unknown genes. Since the genes usually belong to multiple functional families, fuzzy clustering methods are more appropriate than the conventional hard clustering methods which assi...

In this research, the traditional fuzzy ISODATA ( FI ) algorithm is integrated with probabilistic relaxation labeling ( PRL ) algorithm to form a new clustering algorithm called relaxed fuzzy ISODATA ( RFI ). During the clustering process, both the fuzzy membership function values and local contextual information are employed for grouping data into clusters. The RFI algorithm is considered for ...

There are about a hundred sulci in the human brain and over a hundred billion whitematter fibers. These two anatomical structures differ in their number, their physicalarrangements and in the function they serve but they do share a common geometricdescription: they are both open continuous curves. This thesis is a study of how thephysical attributes of open curves can be used to...

This paper presents the insights of imbalanced public bicycle distributions, i.e. unable to pick up/return bikes due to empty/full stations through the analysis of spatio-temporal activity patterns of bike stations. YouBike, the public bikesharing system of Taipei City was examined. Taking advantage of Open Data policy, the changes of the number of available bikes across all stations were colle...