Analysis and design of non-linear filters based on cubic spline function
Hongke Zhang · Computer Engineering and Applications Journal · 2008
The paper presents a new method to design a predictive filter which suits to analyze non-stationary data.The processed data are approximated by cubic spline function.The predictive filter is constructed with the true value and the observation value of each observation point.The designed filter can perform adaptive analysis to the observation data,and is able to implement multi-resolution analysis as wavelet transform.The paper discusses the derivation of the filter in detail and analyzes its amplitude-frequency characteristics,and then presents the decomposition and composition structure when using the filter to analyze data.Simulations are performed and the experimental results show the entropy of the coefficients produced by the discussed algorithm is less than that by CDF5/3,so it is an effective analysis method for nonstationary data.