Title :
MISEP-an ICA method for linear and nonlinear mixtures, based on mutual information
Author :
Almeida, Luís B.
Author_Institution :
Instituto Superior Tecnico, Lisbon, Portugal
fDate :
6/24/1905 12:00:00 AM
Abstract :
Presents MISEP, an independent components analysis method for linear and nonlinear mixtures. The method is based on the minimization of the mutual information of the estimated components, and can be seen as an extension of the well known INFOMAX method in two aspects: (1) allowing the analysis of nonlinear mixtures, and (2) automatically estimating the optimal nonlinearities to be used at the outputs during learning. The resulting ICA method consists of the training of a single specialized multilayer perceptron, optimized according to a single objective function: the output entropy. Some examples of the application of the method are given
Keywords :
entropy; learning (artificial intelligence); maximum likelihood estimation; minimisation; multilayer perceptrons; statistics; ICA method; MISEP; learning; linear mixtures; minimization; mutual information; nonlinear mixtures; optimal nonlinearities; specialized multilayer perceptron; Density measurement; Ear; Entropy; Independent component analysis; Information analysis; Multidimensional systems; Multilayer perceptrons; Mutual information; Optimization methods; Vectors;
Conference_Titel :
Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on
Conference_Location :
Honolulu, HI
Print_ISBN :
0-7803-7278-6
DOI :
10.1109/IJCNN.2002.1005513
