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The performance of two mothers wavelets in function approximation.

Research into Wavelet Neural Networks was conducted on numerous occasions in the past. Based on previous research, it was noted that the Wavelet Neural Network could reliably be used for function approximation. The research conducted included comparisons between the mother functions of the Wavelet...

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Main Authors: Mohd Idris, Mohd Fazril Izhar, Ahmad Dahlan, Zaki, Jusoff, Kamaruzaman
Format: Article
Language:English
Published: Canadian Center of Science and Education 2009
Online Access:http://psasir.upm.edu.my/id/eprint/17268/1/The%20performance%20of%20two%20mothers%20wavelets%20in%20function%20approximation.pdf
http://psasir.upm.edu.my/id/eprint/17268/
http://ccsenet.org/journal/index.php/jmr/article/view/3778/3388
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spelling my.upm.eprints.172682015-10-23T03:16:39Z http://psasir.upm.edu.my/id/eprint/17268/ The performance of two mothers wavelets in function approximation. Mohd Idris, Mohd Fazril Izhar Ahmad Dahlan, Zaki Jusoff, Kamaruzaman Research into Wavelet Neural Networks was conducted on numerous occasions in the past. Based on previous research, it was noted that the Wavelet Neural Network could reliably be used for function approximation. The research conducted included comparisons between the mother functions of the Wavelet Neural Network namely the Mexican Hat, Gaussian Wavelet and Morlet Functions. The performances of these functions were estimated using the Normalised Square Root Mean Squared Error (NSRMSE) performance index. However, in this paper, the Root Mean Squared Error (RMSE) was used as the performance index. In previous research, two of the best mother wavelets for function approximations were determined to be the Gaussian Wavelet and Morlet functions. An in-depth investigation into the two functions was conducted in order to determine which of these two functions performed better under certain conditions. Simulations involving one-dimension and two-dimension were done using both functions. In this paper, we can make a specifically interpretation that Gaussian Wavelet can be used for approximating function for the function domain [−1, 1]. While Morlet function can be used for big domain. All simulations were done using Matlab V6.5. Canadian Center of Science and Education 2009 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/17268/1/The%20performance%20of%20two%20mothers%20wavelets%20in%20function%20approximation.pdf Mohd Idris, Mohd Fazril Izhar and Ahmad Dahlan, Zaki and Jusoff, Kamaruzaman (2009) The performance of two mothers wavelets in function approximation. Journal of Mathematics Research, 1 (2). pp. 135-143. ISSN 1916-9795 http://ccsenet.org/journal/index.php/jmr/article/view/3778/3388
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description Research into Wavelet Neural Networks was conducted on numerous occasions in the past. Based on previous research, it was noted that the Wavelet Neural Network could reliably be used for function approximation. The research conducted included comparisons between the mother functions of the Wavelet Neural Network namely the Mexican Hat, Gaussian Wavelet and Morlet Functions. The performances of these functions were estimated using the Normalised Square Root Mean Squared Error (NSRMSE) performance index. However, in this paper, the Root Mean Squared Error (RMSE) was used as the performance index. In previous research, two of the best mother wavelets for function approximations were determined to be the Gaussian Wavelet and Morlet functions. An in-depth investigation into the two functions was conducted in order to determine which of these two functions performed better under certain conditions. Simulations involving one-dimension and two-dimension were done using both functions. In this paper, we can make a specifically interpretation that Gaussian Wavelet can be used for approximating function for the function domain [−1, 1]. While Morlet function can be used for big domain. All simulations were done using Matlab V6.5.
format Article
author Mohd Idris, Mohd Fazril Izhar
Ahmad Dahlan, Zaki
Jusoff, Kamaruzaman
spellingShingle Mohd Idris, Mohd Fazril Izhar
Ahmad Dahlan, Zaki
Jusoff, Kamaruzaman
The performance of two mothers wavelets in function approximation.
author_facet Mohd Idris, Mohd Fazril Izhar
Ahmad Dahlan, Zaki
Jusoff, Kamaruzaman
author_sort Mohd Idris, Mohd Fazril Izhar
title The performance of two mothers wavelets in function approximation.
title_short The performance of two mothers wavelets in function approximation.
title_full The performance of two mothers wavelets in function approximation.
title_fullStr The performance of two mothers wavelets in function approximation.
title_full_unstemmed The performance of two mothers wavelets in function approximation.
title_sort performance of two mothers wavelets in function approximation.
publisher Canadian Center of Science and Education
publishDate 2009
url http://psasir.upm.edu.my/id/eprint/17268/1/The%20performance%20of%20two%20mothers%20wavelets%20in%20function%20approximation.pdf
http://psasir.upm.edu.my/id/eprint/17268/
http://ccsenet.org/journal/index.php/jmr/article/view/3778/3388
_version_ 1643826465219805184
score 13.244368

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