In this study, the authors propose a novel component-wise variable step-size (cvss) diffusiondistributedalgorithm for estimating a specific parameter over sensor networks. The novelty of the cvssalgorithm is that s...
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In this study, the authors propose a novel component-wise variable step-size (cvss) diffusiondistributedalgorithm for estimating a specific parameter over sensor networks. The novelty of the cvssalgorithm is that step-sizes vary from each other on different components at each iteration. They derive the steady-state value of global mean-square deviation (MSD) and relative MSD (RMSD). In the numerical simulations, they compare the proposed cvssalgorithm with several other least mean square (LMS) algorithms. Results show that, when compared with these other algorithms, the cvssalgorithm can effectively reduce steady-state value and speed up convergence rate of RMSD while not sacrificing the convergence rate of MSD. Results also reveal that the proposed cvssalgorithm can achieve reduced difference of steady-state values of relative estimation error on various components.
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