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New Estimation and Inferential Methods for Functional Connectivity Analysis
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| 자료유형 | 학위논문 |
|---|---|
| 서명/저자사항 | New Estimation and Inferential Methods for Functional Connectivity Analysis. |
| 개인저자 | DiLernia, Andrew S. |
| 단체저자명 | University of Minnesota. Biostatistics. |
| 발행사항 | [S.l.]: University of Minnesota., 2021. |
| 발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2021. |
| 형태사항 | 110 p. |
| 기본자료 저록 | Dissertations Abstracts International 83-03B. Dissertation Abstract International |
| ISBN | 9798538117406 |
| 학위논문주기 | Thesis (Ph.D.)--University of Minnesota, 2021. |
| 일반주기 |
Source: Dissertations Abstracts International, Volume: 83-03, Section: B.
Advisor: Zhang, Lin;Fiecas, Mark. |
| 이용제한사항 | This item must not be sold to any third party vendors. |
| 일반주제명 | Biostatistics. Medical imaging. Statistics. Physiology. Simulation. Schizophrenia. Estimates. Magnetic resonance imaging. Seeds. Mental disorders. Brain. Data analysis. Noise. Methods. Three dimensional imaging. Clustering. Time series. Applied mathematics. Neurosciences. Psychobiology. Clinical psychology. |
| 언어 | 영어 |
| 바로가기 | 
: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
