Application of fast orthogonal search for the design of RBFNN

This paper addresses the use of a fast orthogonalization process to find the nodes of an RBF network which produce the best match to a target function. Several applications of RBF networks using this fast orthogonal search technique have been investigated and a classification problem is presented. The problem involves classification of human chromosomes, which is a highly complicated 30 dimensional and 24 class problem. Experimental results show that the fast orthogonal search technique not only outperforms the traditional technique, but it also uses much less time and effort.