TRANSIENT ANALYSIS OF CLUSTERED MULTITASK DIFFUSION RLS ALGORITHM
Wei Gao, Jie Chen, Wentao Shi, Qunfei Zhang, Cedric Richard
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In this paper, we propose a novel clustered multitask diffusion RLS (MT-DRLS) algorithm over network to further improve the performance of its counterpart, the multitask diffusion LMS (MT-DLMS) algorithm. Its transient behavior is investigated, in the mean and mean-square error sense. Simulation results illustrate the significant improvement of the MT-DRLS over the MT-DLMS in terms of convergence rate and steady-state error, as well as the accuracy of the theoretical findings.