论文部分内容阅读
针对非线性自适应混沌信号去噪算法的参数优化问题,考虑到最优滤波窗长受到不同因素的影响,为提高该算法的自适应性,提出一种滤波窗长自动最优化的判决准则.依据混沌信号和噪声自相关函数的不同,首先采用不同窗长对含噪混沌信号进行去噪,然后计算每个窗长对应的残差自相关度(RAD),最后通过对最小RAD所对应的窗长进行一定比例收缩实现窗长的最优化.仿真结果表明,该判决准则能够在不同条件下对滤波窗长进行有效的自动最优化,提高了混沌信号去噪算法的自适应性.
Aiming at the parameter optimization problem of nonlinear adaptive chaotic signal de-noising algorithm, considering that the optimum filter window length is affected by different factors, a new filter window auto-optimization decision criterion is proposed to improve the adaptiveness of the algorithm. According to the difference of the autocorrelation function between the chaotic signal and the noise, firstly, the noise-free chaotic signals are denoised with different window lengths, and then the residual auto-correlation (RAD) corresponding to each window length is calculated. Finally, Window length to achieve a certain percentage of shrinkage to optimize the window length.The simulation results show that the decision criterion can effectively optimize the filter window length under different conditions and improve the adaptiveness of the chaotic signal denoising algorithm.