Study on Separation of Underwater Vehicle Noise Based on Blind Source Separation
Abstract
Aiming at the study of underwater vehicle noise extraction in the measurement, a method based on blind source separation (BBS) is presented, and the kernel independent component analysis (KICA) is used in the separation of underwater vehicle noise. The principle and algorithm is introduced and the simulation is carried on to compare with the traditional ICA algorithm in BBS. The simulation results show that KICA not only separates the underwater vehicle noise effectively but also is more accurate than the traditional ICA algorithm.
Keywords
Blind source separation, Kernel independent component analysis, Underwater vehicle.
DOI
10.12783/dtcse/ica2019/30749
10.12783/dtcse/ica2019/30749
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