References

Bateman, H. and A. Erdelyi, 1974. Higher Transcendental Functions. Vol. 2, McGraw-Hill, New York, USA.,.

Bhaya, E. and O.A. Sammak, 2016. Approximation by regular neural networks in terms of Dunkl transform. Res. J. Appl. Sci., 11: 933-941.
Direct Link  |  

Chen, T.P. and H. Chen, 1995. Approximation capability to function of several variables, nonlinear functionals and operators by radial basis function neural networks. IEEE. Trans. Neural Netw., 6: 904-910.
CrossRef  |  Direct Link  |  

Chui, C.K. and X. Li, 1992. Approximation by ridge functions and neural networks with one hidden layer. J. Approximation Theor., 70: 131-141.
Direct Link  |  

Funahashi, K.I., 1989. On the approximate realization of continuous mappings by neural networks. Neural Networks, 2: 183-192.
CrossRef  |  Direct Link  |  

Hahm, N. and B.I. Hong, 2004. An approximation by neural networks with a fixed weight. Comput. Math. Appl., 47: 1897-1903.
Direct Link  |  

Hornik, K., M. Stinchcombe and H. White, 1989. Multilayer feedforward networks are universal approximators. Neural Networks, 2: 359-366.
CrossRef  |  

Kurkova, V., 1995. Approximation of functions by perceptron networks with bounded number of hidden units. Neural Netw., 8: 745-750.
Direct Link  |  

Leshno, M., V. Lin, A. Pinks and S. Schochen, 1993. Multilayer feedforward networks with a nonpolynomial activation function can approximate any function. Neural Netw., 6: 861-867.
Direct Link  |  

Li, F., 2008. Function approximation by neural networks. Adv. Neural Netw., 5263: 384-390.
Direct Link  |  

Li, X., 1998. On simultaneous approximations by radial basis function neural networks. Appl. Math. Comput., 95: 75-89.
Direct Link  |  

Liu, B. and J. Si, 1994. The best approximation to C/sup 2/functions and its error bounds using regular-center Gaussian networks. IEEE. Trans. Neural Netw., 5: 845-847.
CrossRef  |  PubMed  |  Direct Link  |  

Mhaskar, H.N. and C.A. Micchelli, 1992. Approximation by superposition of sigmoidal and radial basis functions. Adv. Appl. Math., 13: 350-373.
Direct Link  |  

Park, J. and I.W. Sandberg, 1991. Universal approximation using radial-basis-function networks. Neural Comput., 3: 246-257.
CrossRef  |  Direct Link  |  

Scarselli, F. and A.C. Tsoi, 1998. Universal approximation using feed forward neural networks: A survey of some existing methods and some new results. Neural Netw., 11: 15-37.
Direct Link  |  

Xingui, H. and X. Shaohua, 1995. Process Neural Networks, Theory and Applications. Springer, Berlin, Germany,.