A Local Linear Wavelet Neural Network Based on a Bayesian Design Method

2009 ◽  
Vol 129 (7) ◽  
pp. 1356-1362
Author(s):  
Kunikazu Kobayashi ◽  
Masanao Obayashi ◽  
Takashi Kuremoto
Keyword(s):  
Neural Network ◽  
Design Method ◽  
Wavelet Neural Network ◽  
Bayesian Design ◽  
Local Linear

Time-series prediction using a local linear wavelet neural network

2006 ◽  
Vol 69 (4-6) ◽  
pp. 449-465 ◽  
Author(s):  
Yuehui Chen ◽  
Bo Yang ◽  
Jiwen Dong
Keyword(s):  
Neural Network ◽  
Time Series ◽  
Time Series Prediction ◽  
Wavelet Neural Network ◽  
Local Linear

Local linear wavelet neural network for breast cancer recognition

2011 ◽  
Vol 22 (1) ◽  
pp. 125-131 ◽  
Author(s):  
M. R. Senapati ◽  
A. K. Mohanty ◽  
S. Dash ◽  
P. K. Dash
Keyword(s):  
Breast Cancer ◽  
Neural Network ◽  
Wavelet Neural Network ◽  
Local Linear

DESIGN AN ADAPTIVE WAVELET NEURAL NETWORK CONTROLLER FOR A TWO-WHEELED MOBILE ROBOT LIKE VEHICLE

2014 ◽  
Vol 23 (09) ◽  
pp. 1450133 ◽  
Author(s):  
ALIREZA SAFA ◽  
GHASEM ALIZADEH ◽  
HAMID SHIRI
Keyword(s):  
Neural Network ◽  
Mobile Robot ◽  
Design Method ◽  
External Disturbance ◽  
Approximation Error ◽  
Wavelet Neural Network ◽  
Wheeled Mobile Robot ◽  
Adaptive Backstepping ◽  
Adaptive Wavelet ◽  
Neural Network Controller

This paper presents an analytical approach to design an adaptive backstepping wavelet neural network (WNN)-based controller for global asymptotic stabilization of a two-wheeled mobile robot (TWMR). It is assumed that the dynamics model is unknown, and also system exposed to an external disturbance. The design method is based on the concept of backstepping method. At the first level, adaptive backstepping controller is employed. This controller is taking advantage of WNN identifier for estimating of unknown plant dynamics. Moreover, since the adaption laws of controller are extracted in sense of Lyapunov function, the stability of closed loop is guaranteed. At the second level, robust controller is combined with primary controller, which results L2 tracking performance and comforts lumped uncertainties exit in control system due to approximation error and external disturbance. Finally, a numerical example for the proposed control scheme is presented.

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