Acta mathematica scientia,Series A ›› 2010, Vol. 30 ›› Issue (3): 848-856.

• Articles • Previous Articles     Next Articles

The Geometric Rate of Approximation of Neural Network in Lp-Space

 YU Guo-Hua   

  1. Faculty of Science, Ningbo University, Zhejiang Ningbo 315211
  • Received:2007-12-11 Revised:2009-12-22 Online:2010-05-25 Published:2010-05-25
  • Supported by:

    国家自然科学基金(10471069)和浙江省教育厅科研基金(20051778)资助

Abstract:

This paper is devoted to the investigation of approximation of neural network in Lp-space. The convex greedy iteration method is applied to a class of functions that satisfy the so-called "δ-angular condition'' in Lp-space. We show that the rate of approximation is of order o(qn) for some 0<q<1, which extends the result of [1] to Lp-space.

Key words: Neural networks, Lp-space, Approximation, Geometric rate

CLC Number: 

  • 41A20
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