상세정보
Export to Refworks부가기능
Topics in Harmonic Analysis, Sparse Representations, and Data Analysis
상세 프로파일
| 자료유형 | 학위논문 |
|---|---|
| 서명/저자사항 | Topics in Harmonic Analysis, Sparse Representations, and Data Analysis. |
| 개인저자 | Li, Weilin. |
| 단체저자명 | University of Maryland, College Park. Mathematics. |
| 발행사항 | [S.l.]: University of Maryland, College Park., 2018. |
| 발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2018. |
| 형태사항 | 170 p. |
| 기본자료 저록 | Dissertation Abstracts International 79-12B(E). Dissertation Abstract International |
| ISBN | 9780438153776 |
| 학위논문주기 | Thesis (Ph.D.)--University of Maryland, College Park, 2018. |
| 일반주기 |
Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B.
Advisers: John J. Benedetto |
| 요약 | Classical harmonic analysis has traditionally focused on linear and invertible transformations. Motivated by modern applications, there is a growing interest in non-linear analysis and synthesis operators. This thesis encompasses applications of |
| 요약 | The first focus of this thesis deals with scattering transforms, which are particular realizations of convolutional neural networks. While the latter uses trained convolution kernels, scattering transforms use fixed ones, and this simplification |
| 요약 | The second focus of this thesis pertains to the mathematical foundations of super-resolution, which is concerned with the recovery of fine details from low-resolution observations. This imaging model can be mathematically formulated as an ill-po |
| 일반주제명 | Mathematics. Applied mathematics. |
| 언어 | 영어 |
| 바로가기 | 
: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
