Title :
An unbiased and cost-effective leaky-LMS filter
Author :
Nascimento, Vitor H. ; Sayed, Ali H.
Author_Institution :
Dept. of Electr. Eng., California Univ., Los Angeles, CA, USA
Abstract :
We propose a modified leaky-LMS filter that ensures stability of the estimates w(k) in the presence of bounded noise, without introducing any bias term and with the added cost of only a comparison and a multiplication per iteration when compared to the classical LMS algorithm. The new algorithm is further shown to converge for l/sub p/ noise and persistently exciting regressors. It also provides bounded estimates even in finite precision arithmetic. The stability and convergence properties of the new algorithm are established through a deterministic analysis that is based on the Lyapunov theory for the stability of nonlinear difference equations.
Keywords :
adaptive filters; adaptive signal processing; digital arithmetic; filtering theory; least mean squares methods; numerical stability; LMS algorithm; Lyapunov theory; adaptive filter; bounded estimates; bounded noise; convergence properties; cost effective leaky LMS filter; deterministic analysis; finite precision arithmetic; modified leaky LMS filter; nonlinear difference equations stability; regressors; unbiased leaky LMS filter; Adaptive filters; Computational efficiency; Computational modeling; Convergence; Degradation; Difference equations; Fixed-point arithmetic; Least squares approximation; Stability; Upper bound;
Conference_Titel :
Signals, Systems and Computers, 1996. Conference Record of the Thirtieth Asilomar Conference on
Conference_Location :
Pacific Grove, CA, USA
Print_ISBN :
0-8186-7646-9
DOI :
10.1109/ACSSC.1996.599109
