Kohonen and CPANN Toolbox (for Matlab)

The Kohonen and CPANN toolbox is a collection of MATLAB modules for developing Kohonen Maps and Counterpropagation Artificial Neural networs (CPANNs), Supervised Kohonen networks and XY-fused networks. These are well known neural networks aimed to cluster analysis and the study of data structure (Kohonen Maps) and to the data classification (CPANNs, Supervised Kohonen networks and XY-fused networks). A graphical user interface (GUI), which allows an easy model calculation and analysis of results, is also provided with the toolbox.

Help files
HTML files are provided toghter with the MATLAB files in order to help the user. The HTML help provides some underlying information on Kohonen Maps and CPANNs (see Theory section); it also explains how to prepare your data, how to handle the Neural Network settings and how to calculate the models. An example of analysis (on the classical IRIS data set) is shown. Finally, some bibliographic references to Kohonen Maps and CPANNs are given.

Conditions and warranty
The toolbox is freeware and may be used (but not modified) if proper reference is given to the authors. Preferably refer to the followign papers:
Ballabio D, Consonni V, Todeschini R. (2009) The Kohonen and CP-ANN toolbox: a collection of MATLAB modules for Self Organizing Maps and Counterpropagation Artificial Neural Networks. Chemometrics and Intelligent Laboratory Systems, 98, 115-122
Ballabio D, Vasighi M. (2012) A MATLAB Toolbox for Self Organizing Maps and supervised neural network learning strategies. Chemometrics and Intelligent Laboratory Systems, 118, 24-32
In short, no guarantees, whatsoever, are given for the quality of this toolbox or for the consequences of its use. It is inevitable that there will be some bugs, but we have tried to test the algorithms thoroughly.

Download
Fill in the following form. Your personal data will be used only for notification via email of new releases of the toolbox and will not be communicated to external third parties. Once the form has been submitted, download the rar file containing the toolbox on a local folder, unzip the rar file and extract all the Matlab modules in a unique folder. Before starting calculations, please read the HELP files provided in HTML format. A complete guide on how to calculate models is provided.