Abstract. In this paper, we present the application of a neural network for events classification in a high-energy physics experiment. As a network model we use a multi-layer perceptron with a dynamic topology adjustment algorithm. Our solution covers both adding new hidden neuron units and removing unnecessary units. Neural network results are compared to the standard kinematical cuts techniq1guuuuue and to the well-known k-nearest neighbour classifier.

Keywords: neural network, pattern recognition, classification, high-energy physics, spin structure

Print publication: Issue 8 (August 2007)
Received 31 October 2006, in final form 10 January 2007
Published 6 July 2007