서브메뉴
검색
An Information Field Theory Approach to Engineering Inverse Problems
An Information Field Theory Approach to Engineering Inverse Problems
상세정보
- 자료유형
- 학위논문 서양
- 최종처리일시
- 20250211151407
- ISBN
- 9798342101554
- DDC
- 530
- 서명/저자
- An Information Field Theory Approach to Engineering Inverse Problems
- 발행사항
- [Sl] : Purdue University, 2024
- 발행사항
- Ann Arbor : ProQuest Dissertations & Theses, 2024
- 형태사항
- 144 p
- 주기사항
- Source: Dissertations Abstracts International, Volume: 86-04, Section: B.
- 주기사항
- Advisor: Bilionis, Ilias.
- 학위논문주기
- Thesis (Ph.D.)--Purdue University, 2024.
- 초록/해제
- 요약Inverse problems in infinite dimensions are ubiquitously encountered across the scien- tific disciplines. These problems are defined by the need to reconstruct continuous fields from incomplete, noisy measurements, which oftentimes leads to ill-posed problems. Almost universally, the solutions to these problems are constructed in a Bayesian framework. How- ever, in the infinite-dimensional setting, the theory is largely restricted to the Gaussian case, and the treatment of prior physical knowledge is lacking. We develop a new framework for Bayesian reconstruction of infinite-dimensional fields which encodes our physical knowledge directly into the prior, while remaining in the continuous setting. We then prove various characteristics of the method, including situations in which the problems we study have unique solutions under our framework. Finally, we develop numerical sampling schemes to characterize the various objects involved.
- 일반주제명
- Physics
- 일반주제명
- Success
- 일반주제명
- Inverse problems
- 일반주제명
- Neural networks
- 일반주제명
- Navier-Stokes equations
- 일반주제명
- Engineering
- 일반주제명
- Euclidean space
- 일반주제명
- Theorems
- 일반주제명
- Geometry
- 일반주제명
- Parameter estimation
- 일반주제명
- Mathematics
- 기타저자
- Purdue University.
- 기본자료저록
- Dissertations Abstracts International. 86-04B.
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
008250123s2024 us c eng d■001000017161520
■00520250211151407
■006m o d
■007cr#unu||||||||
■020 ▼a9798342101554
■035 ▼a(MiAaPQ)AAI31285084
■035 ▼a(MiAaPQ)25631868
■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a530
■1001 ▼aAlberts, Alexander.
■24513▼aAn Information Field Theory Approach to Engineering Inverse Problems
■260 ▼a[Sl]▼bPurdue University▼c2024
■260 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2024
■300 ▼a144 p
■500 ▼aSource: Dissertations Abstracts International, Volume: 86-04, Section: B.
■500 ▼aAdvisor: Bilionis, Ilias.
■5021 ▼aThesis (Ph.D.)--Purdue University, 2024.
■520 ▼aInverse problems in infinite dimensions are ubiquitously encountered across the scien- tific disciplines. These problems are defined by the need to reconstruct continuous fields from incomplete, noisy measurements, which oftentimes leads to ill-posed problems. Almost universally, the solutions to these problems are constructed in a Bayesian framework. How- ever, in the infinite-dimensional setting, the theory is largely restricted to the Gaussian case, and the treatment of prior physical knowledge is lacking. We develop a new framework for Bayesian reconstruction of infinite-dimensional fields which encodes our physical knowledge directly into the prior, while remaining in the continuous setting. We then prove various characteristics of the method, including situations in which the problems we study have unique solutions under our framework. Finally, we develop numerical sampling schemes to characterize the various objects involved.
■590 ▼aSchool code: 0183.
■650 4▼aPhysics
■650 4▼aPartial differential equations
■650 4▼aCoordinate transformations
■650 4▼aSuccess
■650 4▼aInverse problems
■650 4▼aNeural networks
■650 4▼aNavier-Stokes equations
■650 4▼aEngineering
■650 4▼aEuclidean space
■650 4▼aTheorems
■650 4▼aGeometry
■650 4▼aParameter estimation
■650 4▼aMathematics
■690 ▼a0537
■690 ▼a0605
■690 ▼a0800
■690 ▼a0405
■71020▼aPurdue University.
■7730 ▼tDissertations Abstracts International▼g86-04B.
■790 ▼a0183
■791 ▼aPh.D.
■792 ▼a2024
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17161520▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
