Analysis of the TDLMS algorithm operating in a nonstationary environment

EDUARDO V KUHN; KOLODZIEJ, JAVIER ERNESTO; SEARA, RUI

DIGITAL SIGNAL PROCESSING

ACADEMIC PRESS INC ELSEVIER SCIENCE

Año: 2015

1051-2004

This paper presents a stochastic analysis of the transform-domain least-mean-square (TDLMS) algorithm operating in a nonstationary environment (time-varying plant) with correlated Gaussian input data, from which the analysis for the stationary environment follows as a special case. In this analysis, accurate model expressions are derived describing the mean weight-error behavior, learning curve, transformed weight-error covariance matrix, steady-state excess mean-square error (EMSE), misadjustment, step size for minimum EMSE, degree of nonstationarity, as well as a relationship between misadjustment and degree of nonstationarity. Based on these model expressions, the impact of the algorithm parameters on its performance is discussed, clarifying the behavior of the algorithm vis-à-vis the nonstationary environment considered. Simulation results are shown confirming the accuracy of the proposed model for both transient and steady-state phases.