Title :
Leaky LMS algorithm: MSE analysis for Gaussian data
Author :
Mayyas, K. ; Aboulnasr, Tyseer
Author_Institution :
Dept. of Electr. Eng., Jordan Univ. of Sci. & Technol., Irbid, Jordan
fDate :
4/1/1997 12:00:00 AM
Abstract :
Despite the widespread usage of the leaky LMS algorithm, there has been no detailed study of its performance. This paper presents an analytical treatment of the mean-square error (MSE) performance for the leaky LMS adaptive algorithm for Gaussian input data. The common independence assumption regarding W(n) and X(n) is also used. Exact expressions that completely characterize the second moment of the coefficient vector and algorithm steady-state excess MSE are developed. Rigorous conditions for MSE convergence are also established. Analytical results are compared with simulation and are shown to agree well
Keywords :
Gaussian processes; adaptive signal processing; convergence of numerical methods; least mean squares methods; Gaussian input data; MSE analysis; MSE convergence; coefficient vector; exact expressions; independence assumption; leaky LMS adaptive algorithm; mean-square error performance; second moment; signal analysis; simulation; stationary Gaussian signals; steady-state excess MSE; system identification; Adaptive algorithm; Algorithm design and analysis; Convergence; Data analysis; Interference; Least squares approximation; Performance analysis; Signal processing algorithms; Steady-state; Telephony;
Journal_Title :
Signal Processing, IEEE Transactions on
