CIS Publication Spotlight [Publication Spotlight]
Digital Object Identifier: 10.1109/ TNNLS.2011.2181866 “The definition of a new type of competitive learning scheme realized on large-scale networks is presented which has wide application in artificial neural networks. The model consists of several particles walking within the network and competing with each other to occupy as many nodes as possible, while attempting to reject intruder particles. The particle’s walking rule is composed of a stochastic combination of random and preferential movements. The model has been applied to solve community detection and data clustering problems. Computer simulations reveal that the proposed technique presents high precision of community and cluster detections, as well as low computational complexity. Moreover, an efficient method is developed for estimating the most likely number of clusters by using an evaluator index that monitors the information generated by the competition process itself.”