Title :
Convergence analysis of sign-sign LMS algorithm for adaptive filters with correlated Gaussian data
Author :
Jun, Byung Eul ; Jo Park, Dong ; Kim, Yong Woon
Author_Institution :
Dept. of Electr. Eng., Korea Adv. Inst. of Sci. & Technol., Taejon, South Korea
Abstract :
This paper presents a statistical behavior analysis of a sign-sign least mean square algorithm, which is obtained by clipping both the reference input signal and the estimation error, for adaptive filters with correlated Gaussian data. The study focuses on the derivation of expressions for the first and second moment behavior of the filter coefficient vector and analysis of the filter mean square error. The previous analysis of this type for the sign-sign algorithm is based on the assumption that the input sequence to the adaptive filter is independent, identically distributed Gaussian, but this restriction is removed in our analysis. Theoretical expressions derived are verified numerically through computer simulations for an example of system identification
Keywords :
Gaussian processes; adaptive filters; adaptive signal processing; convergence of numerical methods; correlation methods; filtering theory; identification; least mean squares methods; adaptive filters; computer simulations; convergence analysis; correlated Gaussian data; estimation error clipping; filter coefficient vector; first moment; input sequence; mean square error analysis; reference input signal clipping; second moment; sign-sign LMS algorithm; sign-sign least mean square algorithm; statistical behavior analysis; system identification; Adaptive filters; Algorithm design and analysis; Computer simulation; Convergence; Error analysis; Estimation error; Least mean square algorithms; Least squares approximation; Mean square error methods; Signal analysis;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1995. ICASSP-95., 1995 International Conference on
Conference_Location :
Detroit, MI
Print_ISBN :
0-7803-2431-5
DOI :
10.1109/ICASSP.1995.480498
