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• W3016056543 abstract "This paper studies selecting a subset of the system's output to minimize the state estimation mean square error (MSE). This results in the maximization problem of a set function defined on possible sensor selections subject to a cardinality constraint. We consider to solve it approximately by a greedy search. Since the MSE function is not submodular nor supermodular, the well-known performance guarantees for the greedy solutions do not hold in the present case. Thus, we use the quantities---the submodularity ratio and the curvature---to evaluate the degrees of submodularity and supermodularity of the objective function. By using the properties of the MSE function, we approximately compute these quantities and derive a performance guarantee for the greedy solutions. It is shown that the guarantee is less conservative than those in the existing results." @default.
• W3016056543 created "2020-04-17" @default.
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• W3016056543 date "2020-04-08" @default.
• W3016056543 modified "2023-09-23" @default.
• W3016056543 title "Sensor placement minimizing the state estimation mean square error: Performance guarantees of greedy solutions" @default.
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• W3016056543 doi "https://doi.org/10.48550/arxiv.2004.04355" @default.
• W3016056543 hasPublicationYear "2020" @default.
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