NOVEL STEEPEST DESCENT ADAPTIVE FILTER DERIVED FROM NEW PERFORMANCE-FUNCTION WITH ADDITIONAL EXPONENTIAL TERM

被引:4
作者
JUN, BE [1 ]
PARK, DJ [1 ]
机构
[1] KOREA ADV INST SCI & TECHNOL,DEPT ELECT ENGN,373-1 KUSONG DONG,TAEJON,SOUTH KOREA
关键词
ADAPTIVE FILTERING; STOCHASTIC GRADIENT ALGORITHM; STEEPEST DESCENT METHOD;
D O I
10.1016/0165-1684(94)90207-0
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
A new steepest descent adaptive filter algorithm derived from a newly devised performance index function is presented. The performance function of the new algorithm is introduced from that of the least mean square (LMS) considering that the stochastic steepest descent method utilises a gradient search in order to minimise the performance function iteratively. Through mathematical analyses and computer simulations, it is verified that there are significant improvements in convergence speed and misadjustment error. Nevertheless its computational simplicity and robustness are maintained with little degradation (compared to those of the LMS algorithm). The new algorithm can be interpreted as a new kind of variable step size adaptive algorithm, and in this respect a modified method is proposed in order to reduce the noise caused by fluctuation of the varying step size.
引用
收藏
页码:189 / 199
页数:11
相关论文
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