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Structured Low-rank Matrix Approximation in Signal Processing: Semidefinite Formulations and Entropic First-order Methods
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| 자료유형 | E-Book |
|---|---|
| 개인저자 | Chao, Hsiao-Han. |
| 단체저자명 | University of California, Los Angeles. Electrical Engineering 0303. |
| 서명/저자사항 | Structured Low-rank Matrix Approximation in Signal Processing: Semidefinite Formulations and Entropic First-order Methods. |
| 발행사항 | [S.l.] : University of California, Los Angeles., 2018 |
| 발행사항 | Ann Arbor : ProQuest Dissertations & Theses, 2018 |
| 형태사항 | 151 p. |
| 소장본 주기 | School code: 0031. |
| ISBN | 9780438068841 |
| 일반주기 |
Source: Dissertation Abstracts International, Volume: 79-10(E), Section: B.
Adviser: Lieven Vandenberghe. |
| 요약 | Applications of semidefinite optimization in signal processing are often derived from the Kalman--Yakubovich--Popov lemma and its extensions, which give sum-of-squares theorems of nonnegative trigonometric polynomials and generalized polynomials |
| 요약 | The thesis can be divided into two parts. As a first contribution, we extend the semidefinite penalty formulations in super-resolution applications to more general types of structured low-rank matrix approximations. The penalty functions for str |
| 일반주제명 | Applied mathematics. Electrical engineering. Computer engineering. |
| 언어 | 영어 |
| 기본자료 저록 | Dissertation Abstracts International79-10B(E). Dissertation Abstract International |
| 대출바로가기 | http://www.riss.kr/pdu/ddodLink.do?id=T14999106 |
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| No. | 등록번호 | 청구기호 | 소장처 | 도서상태 | 반납예정일 | 예약 | 서비스 | 매체정보 |
|---|---|---|---|---|---|---|---|---|
| 1 | WE00028413 | 519 | 가야대학교// | 대출가능 |
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