Genetic algorithm with aggressive mutation for feature selection in BCI feature space

Abstract

The aim of this paper is to present a new algorithm for feature selection, called a genetic algorithm with aggressive mutation. The paper presents both the theoretic background of the algorithm and its application for feature selection in the brain–computer interface (BCI) domain. To fully present the potential of the algorithm and to verify its practical usability, it is compared with other methods commonly used in BCI research. The practical application of the proposed algorithm is presented via a benchmark set submitted to the second BCI Competition (data set III—motor imagery).