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• W2766277459 abstract "In this paper, we present a greedy sensor selection algorithm for minimum variance distortionless response (MVDR) beamforming under a modular budget constraint. In particular, we propose a submodular set-function that can be maximized using a linear-time greedy heuristic that is near optimal. Different from the convex formulation that is typically used to solve the sensor selection problem, the method in this paper neither involves computationally intensive semidefinite programs nor convex relaxation of the Boolean variables. While numerical experiments show a comparable performance between the convex and submodular relaxations, in terms of output signal-to-noise ratio, the latter finds a near-optimal solution with a significantly reduced computational complexity." @default.
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• W2766277459 date "2017-08-01" @default.
• W2766277459 modified "2023-09-24" @default.
• W2766277459 title "Near-optimal greedy sensor selection for MVDR beamforming with modular budget constraint" @default.
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• W2766277459 doi "https://doi.org/10.23919/eusipco.2017.8081556" @default.
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