This paper deals with the problem of under-determined convolutive blind source separation. We model the contribution of each source to all mixture channels in the time-frequency d...
In this work, we present a general method for approximating nonlinear transformations of Gaussian mixture random variables. It is based on transforming the individual Gaussians wi...
Abstract-- This paper considers uncertain constrained systems, and develops a method for computing a probabilistic output admissible (POA) set which is a set of initial states prob...
The paper presents a new genetic local search algorithm for multi-objective combinatorial optimization. The goal of the algorithm is to generate in a short time a set of approxima...
Machine learning methods are often used to classify objects described by hundreds of attributes; in many applications of this kind a great fraction of attributes may be totally irr...
Miron B. Kursa, Aleksander Jankowski, Witold R. Ru...