자료유형 | 학위논문 |
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서명/저자사항 | Online Model-Based Estimation for Automated Optical System Alignment and Phase Retrieval Algorithm. |
개인저자 | Fang, Joyce. |
단체저자명 | Cornell University. Mechanical Engineering. |
발행사항 | [S.l.]: Cornell University., 2018. |
발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2018. |
형태사항 | 163 p. |
기본자료 저록 | Dissertation Abstracts International 80-01B(E). Dissertation Abstract International |
ISBN | 9780438342545 |
학위논문주기 | Thesis (Ph.D.)--Cornell University, 2018. |
일반주기 |
Source: Dissertation Abstracts International, Volume: 80-01(E), Section: B.
Adviser: Dmitry Savransky. |
요약 | Online model-based estimation is applied to two major applications in optics: Automated optical component alignment and wavefront reconstruction with simultaneous system parameter estimation. Both applications utilize mechanical perturbation in |
요약 | The first part of this study proposes a novel automated alignment method which improves efficiency and increases the flexibility of an optical system. Current optical systems with automated alignment capabilities are typically designed to includ |
요약 | The second part of this study presents a novel algorithm for phase retrieval and optical system parameter estimation. Many wavefront reconstruction techniques estimate the amplitude and phase from multiple intensity measurements. One can generat |
요약 | We modify and extend the system variable estimation method to serial phase retrieval algorithm. We present the use of iterated extended Kalman filter (IEKF) to estimate the system variables in a multiple-image phase retrieval framework. An itera |
일반주제명 | Engineering. Mechanical engineering. |
언어 | 영어 |
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: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |