Extending self-organizing maps for supervised classification of remotely sensed data

An extended self-organizing map for supervised classification is proposed in this paper.Unlike other traditional SOMs,the model has an input layer,a Kohonen layer,and an output layer.The number of neurons in the input layer depends on the dimensionality of input patterns.The number of neurons in the output layer equals the number of the desired classes.The number of neurons in the Kohonen layer may be a few to several thousands,which depends on the complexity of classification problems and the classificatio...