AANN: an alternative to GMM for pattern recognition

The objective in any pattern recognition problem is to capture the characteristics common to each class from feature vectors of the training data. While Gaussian mixture models appear to be general enough to characterize the distribution of the given data, the model is constrained by the fact that the shape of the components of the distribution is assumed to be Gaussian, and the number of mixtures are

• Type: Journal
• Year: 2002
• Where: NN
• Authors: B. Yegnanarayana, S. P. Kishore
• Keywords: Gaussian Mixture Models, Neural Network, Neural Networks, NN 2002, Pattern Recognition Problem