Interpreting the Contribution of Sensors in Blind Source Extraction by Means of Shapley Values

Guilherme Pelegrina (), Leonardo Duarte and Michel Grabisch
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Guilherme Pelegrina: UNICAMP - Universidade Estadual de Campinas = University of Campinas
Leonardo Duarte: UNICAMP - Universidade Estadual de Campinas = University of Campinas

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Abstract: Several practical applications can be formulated as a problem of estimating a source of interest from a set of mixed data collected by different sensors. Although a lot of effort has been done to address the optimization task in signal extraction, there is a lack in the literature on how to evaluate the contribution of each sensor in the extraction process. In this letter, we propose a model-agnostic approach that can be used to interpret both the contribution of each sensor in the estimated source and the interaction effects between them. Our proposal is based on a solution concept from game theory, called Shapley value. Numerical experiments on synthetic and real data attest the use of our proposal in blind source extraction problems.

Keywords: signal extraction; sensors design; Shapley value (search for similar items in EconPapers)
Date: 2023
Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-04356790v1
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Published in IEEE Signal Processing Letters, 2023, 30, pp.878-882. ⟨10.1109/LSP.2023.3295759⟩

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Working Paper: Interpreting the Contribution of Sensors in Blind Source Extraction by Means of Shapley Values (2023)
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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:halshs-04356790

DOI: 10.1109/LSP.2023.3295759

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