An NLMS Algorithm with Variable Step-Size Uodates through Selective inputs

MasterThis paper presents a variable step-size normalized least-mean-square (VSS-NLMS) algorithm using only one parameter. Numerous VSS-NLMS algorithms lead to fast convergence rate and low misadjustment depend on several parameters that are not simple to tune on practice. The proposed VSS-NLMS algorithm leads to faster convergence rate and low misadjustment though the algorithm uses only one parameter. And the parameter can easily tuned through input data