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Proceedings Paper

Function approximation by polynomial wavelets generated from powers of sigmoids
Author(s): Joao Fernando Marar; Edson C. B. Carvalho Filho; Germano C. Vasconcelos
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Paper Abstract

Wavelet functions have been successfully used in many problems as the activation function of feedforward neural networks [ZB92], [STK92], [PK93]. In this paper, a family of polynomial wavelets generated from powers of sigmoids is described which provides a robust way for designing neural network architectures. It is shown, through experimentation, that function members of this family can present a very good adaptation capability which make them attractive for applications of function approximation. In the experiments carried out, it is observed that only a small number of daughter wavelets is usually necessary to provide good approximation characteristics.

Paper Details

Date Published: 22 March 1996
PDF: 10 pages
Proc. SPIE 2762, Wavelet Applications III, (22 March 1996); doi: 10.1117/12.236043
Show Author Affiliations
Joao Fernando Marar, Univ. Estadual Paulista (Brazil) and Univ. Federal de Pernambuco (Brazil)
Edson C. B. Carvalho Filho, Univ. Federal de Pernambuco (Brazil)
Germano C. Vasconcelos, Univ. Federal de Pernambuco (Brazil)

Published in SPIE Proceedings Vol. 2762:
Wavelet Applications III
Harold H. Szu, Editor(s)

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