[1]LI Yang,ZHONG Shi-sheng.Research on multi-resolution wavelet process neural networks and applications[J].CAAI Transactions on Intelligent Systems,2008,3(3):211-215.
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Research on multi-resolution wavelet process neural networks and applications

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 3 Number of periods: 2008 3 Page number: 211-215 Column: 学术论文—机器学习 Public date: 2008-06-25
Title:
Research on multi-resolution wavelet process neural networks and applications
Author(s):
LI Yang; ZHONG Shi-sheng
Department of Mechanical and Electrical Engineering; Harbin Institute of Technology; Harbin 150001; China
Keywords:
process neuron;  multiresolution analysis;  multiresolution wavelet process neural network;  learning algorithm;  condition monitoring of aeroengine system
CLC:
TP183
DOI:
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Abstract:
We p ropose a multiresolution wavelet p rocess neural network (MWPNN) based on wavelet multiresolu2 tion analysis theory and the p rocess neural network model. It combines their characteristics of delamination, multi2 resolution, and local learning capability. The network, making full use of the comp lementary characteristic ofwave2 let function and scale function, aswell as the ability to handle continuous input signals, can forecast comp licated nonlinear time sequences. The network’s learning algorithm is given. Using an examp le of state monitoring of ex2 haust gas temperature margins of aeroengines, forecasting was performed using the multi2resolution wavelet p rocess neural network. It was found that the p roposed network exhibited good convergence and high accuracy, p roviding an effective way for state monitoring of exhaust gas temperatures of aeroengines
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