基于小波变换的光混沌信号消噪与Lyapunov指数计算

针对动力学方程未知且信噪比小的光混沌信号,采用小波多分辨分解算法对其进行噪音消减.用Lorenz混沌信号对该算法的消噪效果进行了检验.提出利用互信息量法和Cao氏法来改进小数据量法在时间延迟和嵌入维数计算上存在的主观选择性,对经过噪音消减的Lorenz混沌信号利用此改进的小数据量法计算其最大Lyapunov指数.结果表明,信噪比可提高近10 dB左右,最大Lyapunov指数计算误差可减少近30%,并求得半导体放大器光混沌信号的最大Lyapunov指数为0.389 6.

Lyapunov Exponent of Optical Chaos Based on Wavelet Transform

The wavelet multi-resolution decomposition algorithm was used for reducing noise of optical chaos signals with dynamic equation unknown and low SNR.The algorithm was verified by Lorenz chaotic signal.The mutual information algorithm and Cao method were used to reduce the subjective in computing the delay time and embedding dimension when applying the small data method to compute the largest Lyapunov exponent.The largest lyapunov exponent of the de-noised chaos signal was calculated with this improved method.The result shows that the SNR is increased by about 10 dB,and the error of the largest Lyapunov exponent is reduced by 30%.The largest Lyapunov exponent of the optical chaos signal 0.389 6 is obtained with this method.