Learning of Radial Basis Function Networks: Experimental Results
نویسنده
چکیده
We present various learning methods for RBF networks. The standard gradient-based learning is augmented by the weighted norm adaptation. The three-step learning algorithm uses different unsupervised learning algorithms for setting the centroids. Two possible combinations with genetic learning algorithm are considered as well. All learning variants are thoroughly compared on two benchmark tasks. Key-Words: Radial Basis Function Networks, Hybrid learning, Soft computing.
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تاریخ انتشار 2002