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- W2023355577 abstract "A ships position could be detected by its magnetic signature. A crucial issue, regarding this approach for naval vessel monitoring, is the difficulty in defining the appropriate number of magnetic sensors needed and their respective configuration, in order to predict accurately the position of the magnetic mass through the measured magnetic field intensities on a specific boundary. In the present paper, this problem is dealt downscaled at tracing the exact position and orientation of a single dipole. In particular, Neural Networks, properly calibrated, are implemented as a method for the detection of the position and the orientation of a dipole through the measured magnetic field inducted. The results indicate that measurements of two magnetic field sensors at the boundary could provide sufficient information about the dipoles position, with a certainty of 99%." @default.
- W2023355577 created "2016-06-24" @default.
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- W2023355577 date "2014-04-01" @default.
- W2023355577 modified "2023-09-26" @default.
- W2023355577 title "Dipole Positioning Recognition Using Neural Networks" @default.
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- W2023355577 doi "https://doi.org/10.4028/www.scientific.net/kem.605.673" @default.
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