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In this paper a novel distributed algorithm derived from the Generalized Likelihood Ratio is proposed for real time change detection using sensor networks. The algorithm is based on a combination of recursively generated local statistics and a global consensus strategy, and does not require any fusion center. The problem of detection of an unknown change in the mean of an observed random process is...
In this paper a novel distributed recursive algorithm based on the Generalized Likelihood Ratio methodology is proposed for real time change detection using sensor networks. The algorithm is based on a combination of recursively generated local statistics and a global consensus strategy, and does not require any fusion center, so that the state of any node can be tested w.r.t. a given common threshold...
In this paper a novel consensus based distributed recursive algorithm is proposed for real time change detection using sensor networks. The algorithm is based on local statistics generated by geometric moving average control charts, and does not require any fusion center, so that the state of any node can be tested w.r.t. a given common threshold. Convergence of the algorithm to the optimal centralized...
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