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GAO Da-Qi(Institute of Information Science, Jiangsu University of Science and Technology, Zhenjiang 212013)  
How to optimally select the number of hidden nodes of a supervisedfeedforward three-layered neural network using linear basis function (LBF) basedon back-propagation (BP) algorithm is a very important and difficult problem forone to first surmount in applications. To solve it, an empirical formula for initiallyselecting the number of hidden nodes of this kind of networks is summarized and in-duced according to many application examples at home and abroad, and an elaboratemethod for judging whether there exist redundant hidden nodes in the hidden layerof such a selected network is proposed, and further, a detailed deduction in theoryis given. Two examples show that the empirical formula is reliable and that the newjudging method is simple.
【Fund】: 江苏省自然科学基金;;国家教委博士后基金
【CateGory Index】: TP18
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