New gradient methods for sensor selection problems

Zhang De, Mingqiang Li, Feng Zhang and Maojun Fan

International Journal of Distributed Sensor Networks, 2019, vol. 15, issue 3, 1550147719839642

Abstract: In this article, we consider the sensor selection problem of choosing T sensors from a set of m possible sensor measurements. The sensor selection problem is a combinational optimization problem. Evaluating the performance for each possible combination is impractical unless m and T are small. We relax the original selection problem to be a convex optimization problem and describe a projected gradient method with Barzilai–Borwein step size to solve the proposed relaxed problem. Numerical results demonstrate that the proposed algorithm converges faster than some classical algorithms. The solution obtained by the proposed algorithm is closer to the truth.

Keywords: Sensor selection problem; projected gradient method; Barzilai–Borwein step size (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:sae:intdis:v:15:y:2019:i:3:p:1550147719839642

DOI: 10.1177/1550147719839642

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