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C. Chui, X. Li, Approximation by ridge functions and neural networks with one hidden layer,Journal of Approximation Theory, 1992, 70(2), 131-141.[2]韋崗,李華,徐秉錚,關(guān)于前饋多層神經(jīng)網(wǎng)絡(luò)多維函數(shù)逼近能力的一個(gè)定理,電子科學(xué)學(xué)刊,1997,19(4),433-438[3]韋崗,賀前華,歐陽景正,關(guān)于多層感知器的函數(shù)逼近能力,信息與控制,1996,25(6),321-324.[4]K. Hornik, Some results on neural network approximation, Neural Networks, 1993, 6(8), 1069- 1072.[5]J. Park, I. W. Sandberg, Universal approximation using radial-basis-function networks, Neural Comput., 1991, 3(2), 246-257.[6]E. Gelenbe, Y. Feng, K. R. R. Krishnan, Neural network methods for volumetric magnetic reso nance imaging of the human brain, Proc. IEEE., 1996, 84(10), 1529-1543.[7]E. Gelenbe, Random neural networks with negative and positive signals and product form solution, Neural Comput., 1989, 1(4), 502-511.[8]E. Gelenbe, Learning in the recurrent random neural network, Neural Comput., 1993, 5(1), 154- 164.[9]E. Gelenbe, A. Stafylopatis, A. Likas, Associative memory operation of the random network model, in Proc. Int. Conf. Artificial Neural Networks, Helsinki, Finland, 1991, 307-312.[10]E. Gelenbe, Z. H. Mao, Y. D. Li, Function approximation with spiked random networks, IEEE Trans. on Neural Networks, 1999, NN-10(1), 3-9.
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