— This paper shows that the k-means quantization of a signal can be interpreted both as a crisp indicator function and as a fuzzy membership assignment describing fuzzy clusters ...
K-means is a widely used partitional clustering method. A large amount of effort has been made on finding better proximity (distance) functions for K-means. However, the common c...
In this paper, we propose a new context-based method for object recognition. We first introduce a neuro-physiologically motivated visual part detector. We found that the optimal f...
Functionally related genes co-evolve, probably due to the strong selection pressure in evolution. Thus we expect that they are present in multiple genomes. Physical proximity amon...
Topological persistence has proven to be a key concept for the study of real-valued functions defined over topological spaces. Its validity relies on the fundamental property tha...