Among the neural network models RBF(Radial Basis Function) network seems to be quite effective for a pattern recognition task such as handwritten numeral recognition since it is extremely flexible to accommodate various and minute variations in data. Recently we obtained a good recognition rate for handwritten numerals by using an RBF network. In this paper we show how to design an RBF network ...

In this article an attempt is made to study the applicability of a general purpose, supervised feed forward neural network with one hidden layer, namely. Radial Basis Function (RBF) neural network. It uses relatively smaller number of locally tuned units and is adaptive in nature. RBFs are suitable for pattern recognition and classification. Performance of the RBF neural network was also compar...

This paper is concerned with the comparison of three types of Gaussian based Artificial Neural Networks in the very high dimensionality classification problems found in hyperspectral signal processing. In particular, they have been compared for the spectral unmixing problem given the fact that the requirements for this type of classification are very different from other realms in two aspects: ...

The efficiency of pattern recognition (PR) systems using RBF neural networks to implement their recognition function, depends a lot by the training algorithms of these neural networks and especially, by the specific techniques (e.g., supervised, clustering techniques etc.) used for RBF center positioning. Having as starting point the basic property of genetic algorithms (GA) to represent global...