Adaptive Noise Reduction Method for Chaotic Signals Using Dual-Lifting Wavelet Transform

Based on different features between chaotic signals and Gaussian noises, an adaptive noise reduction method is proposed using dual-lifting wavelet transform. The proposed method has two major steps: the estimation of approximation signals and the adaptive choice of detail coefficients. The former is handled by singular spectrum analysis, whereas the latter is analyzed combining with gradient decent algorithm in neural networks. The chaotic signals generated by Lorenz model as well as the observed monthly series of sunspots are respectively applied for simulation analysis, the experimental results show that the performance of the proposed method is superior to that of other methods.