The deformation time series prediction based on wavelet and neural network

In the paper, the research present situation and development in the wavelet neural network model and a novel learning algorithm for wavelet neural network based on extended Kalman filter are discussed. Based on combining the exceptional property of localization of the wavelet transform and characteristics of self-learning of neural networks, the non-line time series model and network architecture model which combines affine transform with revolving transform is discussed .A novel learning algorithm for wavelet neural network based on extended Kalman filter is proposed to predict the deformation of structure. In comparison with the WNN algorithm, the EKF learning algorithm has improved convergence and can provide much more accuracy learning results.