Generalized wavelet neural network model and its application in time series prediction

Ahmad Banakar; Mohammad Fazle Azeem; IEEE

doi:10.1109/IJCNN.2006.246778

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Generalized wavelet neural network model and its application in time series prediction

Ahmad Banakar, Mohammad Fazle Azeem and IEEE

2006 IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORK PROCEEDINGS, VOLS 1-10, pp.882-886

IEEE International Joint Conference on Neural Networks (IJCNN)

01/01/2006

DOI: https://doi.org/10.1109/IJCNN.2006.246778

Abstract

Computer Science

Computer Science, Artificial Intelligence

Science & Technology

Technology

In present scenario, wavelet becomes an emerging tool for the function approximation. Its use improves the performance of neural network as function approximator. By the inspiration of valuable features of wavelets, the presented work propose two types of models in which wavelet and neural networks simultaneously in parallel to each other. First model is obtained by the adding the output of wavelet neurons and neural network neurons, while in second model multiplication is applied. Its application in time series prediction is also proposed in this paper.

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Title: Generalized wavelet neural network model and its application in time series prediction
Creators - without role: Ahmad Banakar - Aligarh Muslim University
Mohammad Fazle Azeem - Aligarh Muslim University
IEEE
Publication Details: 2006 IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORK PROCEEDINGS, VOLS 1-10, pp.882-886
Series: IEEE International Joint Conference on Neural Networks (IJCNN)
Publisher: IEEE
Number of pages: 2
Identifiers: 9923678408331
Academic Unit: King Khalid University
Language: English
Resource Type: Conference proceeding