DocumentCode
2768160
Title
Comparative Study of Different Types of Wavelet Functions in Neural Network
Author
Azeem, M.F. ; Banakar, Ahmad ; Kumar, Vinod
Author_Institution
Aligarh Muslim Univ., Aligarh
fYear
0
fDate
0-0 0
Firstpage
1061
Lastpage
1066
Abstract
Based on the wavelet transform theory, the new notion of the wavelet network is proposed as an alternative to feed forward neural networks for approximating arbitrary nonlinear functions. Boubez employed ortho-normal wavelets; Yamakawa, Uchino and Samatsu proposed two types of new neuron models and named Wavelet Synapse (WS) neuron and Wavelet Activation (WA) function neuron. These models are obtained by modifying the Mc Culloch and Pitts neuron model with non-orthogonal wavelet bases. Comparative study of different type of Wavelet functions is carried out in this paper by applying above two neuron models.
Keywords
feedforward neural nets; function approximation; nonlinear functions; wavelet transforms; feed forward neural network; nonlinear function approximation; nonorthogonal wavelet function; wavelet activation function neuron model; wavelet synapse neuron model; wavelet transform theory; Continuous wavelet transforms; Educational institutions; Intelligent networks; Neural networks; Neurons; Performance analysis; Signal analysis; Signal resolution; Wavelet analysis; Wavelet transforms;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2006. IJCNN '06. International Joint Conference on
Conference_Location
Vancouver, BC
Print_ISBN
0-7803-9490-9
Type
conf
DOI
10.1109/IJCNN.2006.246806
Filename
1716217
Link To Document