Steady-state performance of incremental learning over distributed networks for non-Gaussian data

Li, LeileiZhang, YonggangChambers, Jonathon A.Sayed, Ali H.2017-12-192017-12-192017-12-19200810.1109/ICOSP.2008.4697112https://infoscience.epfl.ch/handle/20.500.14299/143200In 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.Steady-state performance of incremental learning over distributed networks for non-Gaussian datatext::conference output::conference proceedings::conference paper