Paper Info
Title
On the steady-state and tracking analysis of the complex SRLMS algorithm
Abstract
In this paper, the steady-state and tracking behavior of the complex signed regressor least mean square (SRLMS) algorithm are analyzed in stationary and nonstationary environments, respectively. Here, the SRLMS algorithm is analyzed in the presence of complex-valued white and correlated Gaussian input data. Moreover, a comparison between the convergence performance of the complex SRLMS algorithm and the complex least mean square (LMS) algorithm is also presented. Finally, simulation results are presented to support our analytical findings.
Year
Venue
Keywords
2014
Signal Processing Conference
Gaussian noise,least mean squares methods,regression analysis,complex SRLMS algorithm,complex valued white Gaussian input data,correlated Gaussian input data,signed regressor least mean square algorithm,LMS,SRLMS,Steady-state,Tracking
Field
DocType
ISSN
Least mean squares filter,Convergence (routing),Algorithm,Gaussian,Steady state,Non-linear least squares,Gaussian function,Gaussian noise,Recursive least squares filter,Mathematics
Conference
2076-1465
Citations 
PageRank 
References 
0
0.34
2
Authors
2
Name
Order
Citations
PageRank
Faiz, M.M.U.100.68
Azzedine Zerguine234351.98