Hierarchical clustering methods are important in many data mining and pattern recognition tasks. In this paper we present an efficient coarse grained parallel algorithm for Single...
EEG segments recorded during microsleep events were transformed to the frequency domain and were subsequently clustered without the common summation of power densities in spectral ...
In this paper, we present a new algorithm for clustering data in large datasets using image processing approaches. First the dataset is mapped into a binary image plane. The synthe...
Ant-based clustering and sorting is a nature-inspired heuristic for general clustering tasks. It has been applied variously, from problems arising in commerce, to circuit design, t...
Cluster analysis is a technique used in a variety of fields. There are currently various algorithms used for grouping elements that are based on different methods including partiti...