(1) Neural Networks and Adaptive System Research Group, Dept. of Industrial Engineering, University of Perugia, Perugia, Italy;(2) Zentral Institut für Biomedizinische Technik, University of Ulm, Ulm, Germany
Abstract:
In this paper we deal with the problem of approximating the probability density function of a signal by means of adaptive activation function neurons. We compare the proposed approach to the one based on a mixture of kernels and show through computer simulations that comparable results may be obtained with limited expense in computational efforts.