| LDR | | 01662nam u200397 4500 |
| 001 | | 000000418461 |
| 005 | | 20190215162901 |
| 008 | | 181129s2018 |||||||||||||||||c||eng d |
| 020 | |
▼a 9780438006034 |
| 035 | |
▼a (MiAaPQ)AAI10825328 |
| 035 | |
▼a (MiAaPQ)ucla:16781 |
| 040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 247004 |
| 082 | 0 |
▼a 574 |
| 100 | 1 |
▼a Li, Qian. |
| 245 | 10 |
▼a Hierarchical Integration of Heterogeneous Highly Structured Data: The Case of Functional Brain Imaging. |
| 260 | |
▼a [S.l.]:
▼b University of California, Los Angeles.,
▼c 2018. |
| 260 | 1 |
▼a Ann Arbor:
▼b ProQuest Dissertations & Theses,
▼c 2018. |
| 300 | |
▼a 117 p. |
| 500 | |
▼a Source: Dissertation Abstracts International, Volume: 79-10(E), Section: B. |
| 500 | |
▼a Adviser: Donatello Telesca. |
| 502 | 1 |
▼a Thesis (Ph.D.)--University of California, Los Angeles, 2018. |
| 520 | |
▼a Functional brain imaging technologies produce high dimensional data with structured dependency spanning along multiple dimensions. This dissertation focuses on the specific case of Electroencephalography (EEG), even though most methodological de |
| 590 | |
▼a School code: 0031. |
| 650 | 4 |
▼a Biostatistics. |
| 650 | 4 |
▼a Statistics. |
| 690 | |
▼a 0308 |
| 690 | |
▼a 0463 |
| 710 | 20 |
▼a University of California, Los Angeles.
▼b Biostatistics 0132. |
| 773 | 0 |
▼t Dissertation Abstracts International
▼g 79-10B(E). |
| 773 | |
▼t Dissertation Abstract International |
| 790 | |
▼a 0031 |
| 791 | |
▼a Ph.D. |
| 792 | |
▼a 2018 |
| 793 | |
▼a English |
| 856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T14998755
▼n KERIS
▼z 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
| 980 | |
▼a 201812
▼f 2019 |
| 990 | |
▼a ***1012033 |