STOCHASTIC ANALYSIS OF THE LMS ALGORITHM FOR NON-STATIONARY WHITE GAUSSIAN INPUTS

被引:0
|
作者
Bershad, Neil J. [1 ]
Bermudez, Jose C. M. [2 ]
机构
[1] Univ Calif Irvine, Dept Elect Eng & Comp Sci, Irvine, CA 92717 USA
[2] Univ Fed Santa Catarina, Dept Elect Engn, BR-88040900 Florianopolis, SC, Brazil
关键词
Adaptive filters; Analysis; LMS Algorithm; stochastic algorithms;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This paper studies the stochastic behavior of the LMS algorithm for a system identification framework when the input signal is a non-stationary white Gaussian process. The unknown system is modeled by the standard random walk model. An approximate theory is developed which is based upon the instantaneous average power in the adaptive filter taps. The stability of the algorithm is investigated using this model. Monte Carlo simulations of the algorithm provides strong support for the theoretical approximation.
引用
收藏
页码:57 / 60
页数:4
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