Wavelet-Network based on L1-Norm minimisation for learning chaotic time series. Alarcon-Aquino, V., Garcia-Treviño, E., S., Rosas-Romero, R., Ramirez-Cruz, J., F., Guerrero-Ojeda, L., G., & Rodriguez-Asomoza, J. Journal of Applied Research and Technology, 3(03):211-221, 2005.
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Website abstract bibtex
Website abstract bibtex This paper presents a wavelet-neural network based on the L1-norm minimisation for learning chaotic time series. The proposed approach, which is based on multi-resolution analysis, uses wavelets as activation functions in the hidden layer of the wavelet-network. We propose using the L1-norm, as opposed to the L2-norm, due to the well-known fact that the L1-norm is superior to the L2-norm criterion when the signal has heavy tailed distributions or outliers. A comparison of the proposed approach with previous reported schemes using a time series benchmark is presented. Simulation results show that the proposed wavelet-network based on the L1-norm performs better than the standard back-propagation network and the wavelet-network based on the traditional L2-norm when applied to synthetic data.
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abstract = {This paper presents a wavelet-neural network based on the L1-norm minimisation for learning chaotic time series. The proposed approach, which is based on multi-resolution analysis, uses wavelets as activation functions in the hidden layer of the wavelet-network. We propose using the L1-norm, as opposed to the L2-norm, due to the well-known fact that the L1-norm is superior to the L2-norm criterion when the signal has heavy tailed distributions or outliers. A comparison of the proposed approach with previous reported schemes using a time series benchmark is presented. Simulation results show that the proposed wavelet-network based on the L1-norm performs better than the standard back-propagation network and the wavelet-network based on the traditional L2-norm when applied to synthetic data.},
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author = {Alarcon-Aquino, V and Garcia-Treviño, E S and Rosas-Romero, R and Ramirez-Cruz, J F and Guerrero-Ojeda, L G and Rodriguez-Asomoza, J},
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