De-noising-for-Chaotic-Signal

  为了提高小波分析方法在混沌去噪中的自适应能力，对不同尺度下的小波信号设定调节因子，根据混沌序列 关联维的大小确定最优阈值。为了提高寻优效率，采用遗传算法全局自适应搜索最优阈值。利用该方法对Lorenz混沌时 间序列进行了去噪分析，结果表明所提方法是非常有效的。(For the purpose of improving adaptive performance of chaotic signals de-noising with wavelet transform，a floating parameter is set to regulate the threshold of wavelet signal on different scales according to the correlation dimension of chaotic time series．The genetic algorithm is helpful tO obtain global optimum thresholds and tO reduce much time wasted by the adaptive searching computation．De-noising for Chaotic time series generated by Lorenz system is simulated to corn— pare with other methods，and the results showed that the proposed method iS effective)

De-noising for Chaotic Signal.pdf,290350,2016-07-19