conference paper
Steady-state performance of incremental learning over distributed networks for non-Gaussian data
2008
9th International Conference on Signal Processing
In this paper, the steady-state performance of the distributed least mean-squares (dLMS) algorithm within an incremental network is evaluated without the restriction of Gaussian distributed inputs. Computer simulations are presented to verify the derived performance expressions.