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The Consistency of Spectral Clustering With fMRI Data
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| 자료유형 | 학위논문 |
|---|---|
| 서명/저자사항 | The Consistency of Spectral Clustering With fMRI Data. |
| 개인저자 | Moon, Jessie Eunyoung. |
| 단체저자명 | University of Maryland, College Park. Mathematical Statistics. |
| 발행사항 | [S.l.]: University of Maryland, College Park., 2018. |
| 발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2018. |
| 형태사항 | 119 p. |
| 기본자료 저록 | Dissertation Abstracts International 79-11B(E). Dissertation Abstract International |
| ISBN | 9780438158481 |
| 학위논문주기 | Thesis (Ph.D.)--University of Maryland, College Park, 2018. |
| 일반주기 |
Source: Dissertation Abstracts International, Volume: 79-11(E), Section: B.
Advisers: Eric Slud |
| 요약 | Functional magnetic resonance imaging (fMRI) is a non-invasive technique for studying brain activity. It uses the amount of blood flowing through a brain, referred to as the blood oxygenation level dependent (BOLD) signal. However analyzing the |
| 요약 | There are several brain atlases available but researchers observe that fMRI signals are not coherent even within the same area in a brain atlas. Therefore providing parcellation of a brain, especially based on its functional connectivity, is nec |
| 요약 | One of the techniques that are used for a brain parcellation is spectral clustering. It is a well-used technique in many areas of studies, such as physics and engineering. However, its asymptotic behavior, whether spectral clustering will produc |
| 일반주제명 | Statistics. |
| 언어 | 영어 |
| 바로가기 | 
: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
