Steady-state performance of non-negative least-mean-square algorithm and its variants
This work provides incremental analysis for online estimation under non-negativity constraints, complementing previous transient behavior studies.
The authors derived closed-form expressions for the steady-state excess mean-square error of four non-negative least-mean-square algorithms, with simulations confirming the theoretical accuracy.
Non-negative least-mean-square (NNLMS) algorithm and its variants have been proposed for online estimation under non-negativity constraints. The transient behavior of the NNLMS, Normalized NNLMS, Exponential NNLMS and Sign-Sign NNLMS algorithms have been studied in our previous work. In this technical report, we derive closed-form expressions for the steady-state excess mean-square error (EMSE) for the four algorithms. Simulations results illustrate the accuracy of the theoretical results. This is a complementary material to our previous work.