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.