A Noise Cleaning Method for Chaotic Time Series and Its Application in Communication

A new algorithm for filtering highly noisy contaminated chaotic time series is proposed and realized. It is indicated by computer simulation that this algorithm can effectively reduce noise on chaotic signal no mater how parameter of chaos generator varies with time. In comparison with the extended-Kalman-filter-based method, this algorithm has a better filtering performance in the case of low signal-to-noise (SNR) ratios, and has the similar performance in the case of high SNR. In addition, a chaotic modulation communication system is also used to evaluate the performance of the algorithm, the result shows the effectiveness of the method.