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Frozen Gaussian Approximation for Elastic Waves, Seismic Inversion and Deep Learning
Frozen Gaussian Approximation for Elastic Waves, Seismic Inversion and Deep Learning
상세정보
- 자료유형
- 학위논문
- Control Number
- 0015491735
- International Standard Book Number
- 9781088310304
- Dewey Decimal Classification Number
- 004
- Main Entry-Personal Name
- Hateley, James Charles, IV.
- Publication, Distribution, etc. (Imprint
- [Sl] : University of California, Santa Barbara, 2019
- Publication, Distribution, etc. (Imprint
- Ann Arbor : ProQuest Dissertations & Theses, 2019
- Physical Description
- 141 p
- General Note
- Source: Dissertations Abstracts International, Volume: 81-04, Section: B.
- General Note
- Advisor: Yang, Xu.
- Dissertation Note
- Thesis (Ph.D.)--University of California, Santa Barbara, 2019.
- Restrictions on Access Note
- This item must not be sold to any third party vendors.
- Restrictions on Access Note
- This item must not be added to any third party search indexes.
- Summary, Etc.
- 요약The frozen Gaussian approximation (FGA) is an efficient solver for high frequency wave propagation. This work is to generalize the FGA to solve the 3-D elastic wave equation and use it as the forward modeling tool for seismic tomography with high-frequency initial datum. The evolution equation is derived by weak asymptotic analysis in conjunction with projecting onto an orthonormal frame
- Subject Added Entry-Topical Term
- Applied mathematics
- Subject Added Entry-Topical Term
- Geophysics
- Subject Added Entry-Topical Term
- Computer science
- Added Entry-Corporate Name
- University of California, Santa Barbara Mathematics
- Host Item Entry
- Dissertations Abstracts International. 81-04B.
- Host Item Entry
- Dissertation Abstract International
- Electronic Location and Access
- 로그인을 한후 보실 수 있는 자료입니다.
- Control Number
- joongbu:565974
MARC
008200131s2019 c eng d■001000015491735
■00520200217181404
■020 ▼a9781088310304
■035 ▼a(MiAaPQ)AAI13896634
■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a004
■1001 ▼aHateley, James Charles, IV.
■24510▼aFrozen Gaussian Approximation for Elastic Waves, Seismic Inversion and Deep Learning
■260 ▼a[Sl]▼bUniversity of California, Santa Barbara▼c2019
■260 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2019
■300 ▼a141 p
■500 ▼aSource: Dissertations Abstracts International, Volume: 81-04, Section: B.
■500 ▼aAdvisor: Yang, Xu.
■5021 ▼aThesis (Ph.D.)--University of California, Santa Barbara, 2019.
■506 ▼aThis item must not be sold to any third party vendors.
■506 ▼aThis item must not be added to any third party search indexes.
■520 ▼aThe frozen Gaussian approximation (FGA) is an efficient solver for high frequency wave propagation. This work is to generalize the FGA to solve the 3-D elastic wave equation and use it as the forward modeling tool for seismic tomography with high-frequency initial datum. The evolution equation is derived by weak asymptotic analysis in conjunction with projecting onto an orthonormal frame
■590 ▼aSchool code: 0035.
■650 4▼aApplied mathematics
■650 4▼aGeophysics
■650 4▼aComputer science
■690 ▼a0364
■690 ▼a0373
■690 ▼a0984
■71020▼aUniversity of California, Santa Barbara▼bMathematics.
■7730 ▼tDissertations Abstracts International▼g81-04B.
■773 ▼tDissertation Abstract International
■790 ▼a0035
■791 ▼aPh.D.
■792 ▼a2019
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T15491735▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
■980 ▼a202002▼f2020
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