CAJ | 학술논문

给出了一个对离散1/f 噪声信号进行跟踪简单修正的 RLS 算法.正规 RLS 算法或快速 RLS 算法在有限运算精度条件下的收敛性和失调性没有本质区别,它们在有限迭代次数后必定会导致 RLS 滤波器权系数发散,特别是在跟踪非平稳信号时更是如此.鉴于此,通过引入一个非线性函数对 RLS 滤波器输入数据的逆自相关阵予以修正.实验表明该算法具有良好的跟踪非平稳信号以及具有混沌特性的1/f 噪声信号的能力,能有效降低跟踪的平均误差以及方差,且能根据输入数据的变化快速调整滤波器系数,性能比正规 RLS 算法好.对于跟踪 fBm 噪声过程如何动态调节记忆因子的问题,推导了记忆因子与输入信号的自相关矩阵特征值之间的一个关系表达式,这为采用 RLS 算法动态调整记忆因子来跟踪 fBm过程提供了理论依据.
급출료일개대리산1/f 조성신호진행근종간단수정적 RLS 산법.정규 RLS 산법혹쾌속 RLS 산법재유한운산정도조건하적수렴성화실조성몰유본질구별,타문재유한질대차수후필정회도치 RLS 려파기권계수발산,특별시재근종비평은신호시경시여차.감우차,통과인입일개비선성함수대 RLS 려파기수입수거적역자상관진여이수정.실험표명해산법구유량호적근종비평은신호이급구유혼돈특성적1/f 조성신호적능력,능유효강저근종적평균오차이급방차,차능근거수입수거적변화쾌속조정려파기계수,성능비정규 RLS 산법호.대우근종 fBm 조성과정여하동태조절기억인자적문제,추도료기억인자여수입신호적자상관구진특정치지간적일개관계표체식,저위채용 RLS 산법동태조정기억인자래근종 fBm과정제공료이론의거.
@@@@A simple improved RLS algorithm is given to track a discrete-time noised 1/f signal. Formal RLS algorithm or rapid computing RLS algorithm in the limited accuracy under the conditions of disorder and convergence is no essential difference, they are limited in the number of iterations and the RLS filter will lead to weight divergence, particularly in tracking non-stationary signals even more so. In view of this, this paper introduces a non-linear function of RLS filter input data from the inverse correlation matrix to be amended. Experiments show that the algorithm has a good track non-stationary signals as well as the characteristics of chaos with the 1/f noise of the signal capabilities. It can effectively reduce the tracking error, as well as the average variance, and can input data in accordance with the rapid changes in the adjustment of filter coefficients. Performance is better than the regular RLS algorithm. FBm noise for tracking the dynamic process of adjustment factor memory, this paper derives an expression of relation between memory factor and input signal autocorrelation matrix, providing theoretical basis for the RLS algorithm which is used to dynamically adjust the memory factor to track the fBm process.