Share  Bookmark

 Download from




[1] N. Calkin and H. S. Wilf, Recounting the rationals, Amer. Math. Monthly 107 (2000), 360{ 367.
[2] F. Cao and T. Xie, The construction and approximation for feedforword neural networks with xed weights, Proceedings of the ninth international conference on machine learning and cybernetics, Qingdao, 2010, pp. 3164{3168.
[3] T. Chen and H. Chen, Approximation of continuous functionals by neural networks with application to dynamic systems, IEEE Trans. Neural Networks 4 (1993), 910{918.
[4] C. K. Chui and X. Li, Approximation by ridge functions and neural networks with one hidden layer, J. Approx. Theory 70 (1992), 131{141.
[5] C. K. Chui, X. Li and H. N. Mhaskar, Limitations of the approximation capabilities of neural networks with one hidden layer, Adv. Comput. Math. 5 (1996), no. 23, 233{243.
[6] D. Costarelli and R. Spigler, Constructive approximation by superposition of sigmoidal functions, Anal. Theory Appl. 29 (2013), 169{196.
[7] N. E. Cotter, The Stone{Weierstrass theorem and its application to neural networks, IEEE Trans. Neural Networks 1 (1990), 290{295.
[8] G. Cybenko, Approximation by superpositions of a sigmoidal function, Math. Control Signal Systems 2 (1989), 303{314.
[9] S. Draghici, On the capabilities of neural networks using limited precision weights, Neural Networks 15 (2002), 395{414.
[10] K. Funahashi, On the approximate realization of continuous mapping by neural networks, Neural Networks 2 (1989), 183{192.