In this paper,a distributed stochasticapproximationalgorithm is proposed to track the dynamic root of a sum of time-varying regression functions over a *** agent updates its estimate by using the local observation,t...
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In this paper,a distributed stochasticapproximationalgorithm is proposed to track the dynamic root of a sum of time-varying regression functions over a *** agent updates its estimate by using the local observation,the dynamic information of the global root,and information received from its *** with similar works in optimization area,we allow the observation to be noise-corrupted,and the noise condition is much ***,instead of the upper bound of the estimate error,we present the asymptotic convergence result of the *** consensus and convergence of the estimates are ***,the algorithm is applied to a distributed target tracking problem and the numerical example is presented to demonstrate the performance of the algorithm.
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