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《Acta Electronica Sinica》 1997-01
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Modified Nonlinear Least-Square Algorithm for Training Multilayer Feedforward Neural Networks

Sun Shenghe;Huang Yuancan(Dept.of Radio Engineering,Harbin Institute of Technology,Harbin 150001)  
A modified nonlinear least-square algorithm is derived from the approach appending a regularization term to the conventional nonlinear least-square criterion,ineluding the batch and recursive versions. Training multilayer feed forward neural networks using its recursive algorithm,the storage and computational requirements are reduced,and also it can be applicable to the ill-conditioned cases. Simulation demonstrates the superior convergence performance of its recur sive algorithm compared with the back propagation routine
【CateGory Index】: TP183
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