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Distributed conjugate gradient strategies for parameter estimation over sensor networks
This paper presents distributed adaptive algorithms based on the conjugate
gradient (CG) method for distributed networks. Both incremental and diffusion
adaptive solutions are all considered. The distributed conventional (CG) and
modified CG (MCG) algorithms have an improved performance in terms of mean
square error as compared with least-mean square (LMS)-based algorithms and a
performance that is close to recursive least-squares (RLS) algorithms . The
resulting algorithms are distributed, cooperative and able to respond in real
time to changes in the environment.Comment: 5 figures, 5 page