"2691","Faster Training in Nonlinear ICA using MISEP","MISEP has been proposed as a generalization of the INFOMAX method in two directions: (1) handling of nonlinear mixtures, and (2) learning the nonlinearities to be used at the outputs, making the method suitable to the separation of components with a wide range of statistical distributions. In all implementations up to now, MISEP had used multilayer perceptrons (MLPs) to perform the nonlinear ICA operation. Use of MLPs sometimes leads to a relatively slow training. This has been attributed, at least in part, to the non-local character of the MLP's units. This paper investigates the possibility of using a network of radial basis function (RBF) units for performing the nonlinear ICA operation. It shows that the local character of the RBF network's units allows a significant speedup in the training of the system. The paper gives a brief introduction to the basics of the MISEP method, and presents experimental results showing the speed advantage of using an RBF-based network to perform the ICA operation.","http://cogprints.org/2691/","Almeida, Luis B.","UNSPECIFIED","       <span class=\"person_name\">Almeida, Luis B.</span>     (2002)  <a href=\"http://cogprints.org/2691/\"><em>Faster Training in Nonlinear ICA using MISEP.</em></a>       [Conference Paper]         (Unpublished)   ","","2002"