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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| Format: | Article |
| Language: | English |
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Canadian Center of Science and Education
2009
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| Online Access: | http://psasir.upm.edu.my/id/eprint/17268/1/The%20performance%20of%20two%20mothers%20wavelets%20in%20function%20approximation.pdf |
| _version_ | 1825945977243041792 |
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| author | Mohd Idris, Mohd Fazril Izhar Ahmad Dahlan, Zaki Jusoff, Kamaruzaman |
| author_facet | Mohd Idris, Mohd Fazril Izhar Ahmad Dahlan, Zaki Jusoff, Kamaruzaman |
| author_sort | Mohd Idris, Mohd Fazril Izhar |
| collection | UPM |
| 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. |
| first_indexed | 2024-03-06T07:39:55Z |
| format | Article |
| id | upm.eprints-17268 |
| institution | Universiti Putra Malaysia |
| language | English |
| last_indexed | 2024-03-06T07:39:55Z |
| publishDate | 2009 |
| publisher | Canadian Center of Science and Education |
| record_format | dspace |
| spelling | 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 Wavelets (Mathematics) Neural networks (Computer science) Approximation theory |
| spellingShingle | Wavelets (Mathematics) Neural networks (Computer science) Approximation theory Mohd Idris, Mohd Fazril Izhar Ahmad Dahlan, Zaki Jusoff, Kamaruzaman The performance of two mothers wavelets in function approximation. |
| title | 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_short | The performance of two mothers wavelets in function approximation. |
| title_sort | performance of two mothers wavelets in function approximation |
| topic | Wavelets (Mathematics) Neural networks (Computer science) Approximation theory |
| url | http://psasir.upm.edu.my/id/eprint/17268/1/The%20performance%20of%20two%20mothers%20wavelets%20in%20function%20approximation.pdf |
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