Function approximation by polynomial wavelets generated from powers of sigmoids

Joao Fernando Marar; Edson C. B. Carvalho Filho; Germano C. Vasconcelos

doi:10.1117/12.236043

22 March 1996 Function approximation by polynomial wavelets generated from powers of sigmoids

Joao Fernando Marar, Edson C. B. Carvalho Filho, Germano C. Vasconcelos

Proceedings Volume 2762, Wavelet Applications III; (1996) https://doi.org/10.1117/12.236043
Event: Aerospace/Defense Sensing and Controls, 1996, Orlando, FL, United States

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.

Citation Download Citation

Joao Fernando Marar, Edson C. B. Carvalho Filho, and Germano C. Vasconcelos "Function approximation by polynomial wavelets generated from powers of sigmoids", Proc. SPIE 2762, Wavelet Applications III, (22 March 1996); https://doi.org/10.1117/12.236043

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