Wavefield extraction using multi-channel chirplet decomposition | Zendy

Grégoire Le Touzé | Zendy; Paul Cristini | Zendy; Nathalie FavrettoCristini | Zendy; Jacques Blanco | Zendy

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Wavefield extraction using multi-channel chirplet decomposition

Author(s) -

Grégoire Le Touzé,

Paul Cristini,

Nathalie FavrettoCristini,

Jacques Blanco

Publication year - 2010

Publication title -

the journal of the acoustical society of america

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.619

H-Index - 187

eISSN - 1520-8524

pISSN - 0001-4966

DOI - 10.1121/1.3327245

Subject(s) - decomposition , signal (programming language) , inverse problem , inverse , computer science , channel (broadcasting) , acoustics , component (thermodynamics) , extraction (chemistry) , algorithm , decomposition method (queueing theory) , mathematics , physics , telecommunications , mathematical analysis , statistics , geometry , ecology , chemistry , chromatography , biology , programming language , thermodynamics

In acoustical and seismic fields, wavefield extraction has always been a crucial issue to solve inverse problem. Depending on the experimental configuration, conventional methods of wavefield decomposition might no longer likely to hold. In this paper, an original approach is proposed based on a multichannel decomposition of the signal into a weighted sum of elementary functions known as chirplets. Each chirplet is described by physical parameters and the collection of chirplets makes up a large adaptable dictionary, so that a chirplet corresponds unambiguously to one wave component.

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