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Journal of Applied Mathematics
Volume 2014 (2014), Article ID 892653, 6 pages
Research Article

The Construction and Approximation of the Neural Network with Two Weights

College of Mathematics, Hunan University, Changsha 410082, China

Received 16 June 2014; Revised 3 August 2014; Accepted 3 August 2014; Published 13 August 2014

Academic Editor: H. R. Karimi

Copyright © 2014 Zhiyong Quan and Zhengqiu Zhang. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The technique of approximate partition of unity, the way of Fourier series, and inequality technique are used to construct a neural network with two weights and with sigmoidal functions. Furthermore by using inequality technique, we prove that the neural network with two weights can more precisely approximate any nonlinear continuous function than BP neural network constructed in (Chen et al., 2012).