A MATLAB toolbox for Self Organizing Maps and supervised neural network learning strategies
Kohonen maps and Counterpropagation Neural Networks are two of the most popular learning strategies based on Artificial Neural Networks. Kohonen Maps (or Self Organizing Maps) are basically self-organizing systems which are capable to solve the unsupervised rather than the supervised problems, while Counterpropagation Artificial Neural Networks are very similar to Kohonen maps, but an output layer is added to the Kohonen layer in order to handle supervised modelling. Recently, the modifications of Counterpropagation Artificial Neural Networks allowed introducing new supervised neural network strategies, such as Supervised Kohonen Networks and XY-fused Networks. In this paper, the Kohonen and CP-ANN toolbox for MATLAB is described. This is a collection of modules for calculating Kohonen maps and derived methods for supervised classification, such as Counterpropagation Artificial Neural Networks, Supervised Kohonen Networks and XY-fused Networks. The toolbox comprises a graphical user interface (GUI), which allows the calculation in an easy-to-use graphical environment. It aims to be useful for both beginners and advanced users of MATLAB. The use of the toolbox is discussed here with an appropriate practical example. (C) 2012 Elsevier B.V. All rights reserved.
matlab self organizing maps kohonen maps artificial neural networks supervised pattern recognition