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Fast raypath separation based on low-rank matrix approximation in a shallow-water waveguide

Abstract : Subspace algorithms based on higher-order cumulants were developed to achieve high-resolution separation in non-Gaussian processes. However, singular value decomposition (SVD) of a huge matrix is an unavoidable step of these algorithms. The memory space and running time required by the decomposition are super-linear with respect to the size of the matrix, which is prohibitive in terms of practical applications. Thus, in this paper, a fast raypath separation algorithm based on low-rank matrix approximation is proposed in a shallow-water waveguide. The experimental results illustrate that the proposed algorithm dramatically reduces the consumption of time and space, with arbitrarily small error, compared to conventional higher-order cumulant-based algorithms. (C) 2018 Acoustical Society of America
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https://hal-univ-rennes1.archives-ouvertes.fr/hal-01807117
Contributor : Laurent Jonchère <>
Submitted on : Monday, June 4, 2018 - 2:20:45 PM
Last modification on : Tuesday, October 6, 2020 - 8:44:02 AM

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Longyu Jiang, Wenbo Song, Zhe Zhang, Chunfeng Yang, Shijie Wang, et al.. Fast raypath separation based on low-rank matrix approximation in a shallow-water waveguide. Journal of the Acoustical Society of America, Acoustical Society of America, 2018, 143 (4), pp.EL271-EL277. ⟨10.1121/1.5030916⟩. ⟨hal-01807117⟩

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