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A Bayesian Approach to Spike Sorting of Neural Data via Source Localization
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| 자료유형 | E-Book |
|---|---|
| 개인저자 | Greene, Patrick. |
| 단체저자명 | The University of Arizona. Applied Mathematics. |
| 서명/저자사항 | A Bayesian Approach to Spike Sorting of Neural Data via Source Localization. |
| 발행사항 | [S.l.] : The University of Arizona., 2018 |
| 발행사항 | Ann Arbor : ProQuest Dissertations & Theses, 2018 |
| 형태사항 | 117 p. |
| 소장본 주기 | School code: 0009. |
| ISBN | 9780438118256 |
| 일반주기 |
Source: Dissertation Abstracts International, Volume: 79-11(E), Section: B.
Adviser: Kevin K. Lin. |
| 요약 | This dissertation describes a novel mathematical algorithm for extracting spike data and positional information from extracellular electrophysiological neural recordings. By capturing the electrical signals emitted by individual neurons using a |
| 요약 | This dissertation consists of three main components. The primary component is the spike sorting algorithm itself, whose overall mathematical framework is described in chapters 3 and 4. There are two key ideas. The first is the usage of a dipole- |
| 요약 | The second component of this dissertation is a relatively realistic model of the extracellular signal generation and recording process (the "forward model") which we describe in chapter 2. We construct this model in order to better understand th |
| 요약 | The final component of this dissertation is an investigation into the effect of probe geometry and the dipole prior distribution on how well we can estimate neuron positions. This makes extensive use of the forward model described above, and is |
| 일반주제명 | Applied mathematics. Neurosciences. Statistics. |
| 언어 | 영어 |
| 기본자료 저록 | Dissertation Abstracts International79-11B(E). Dissertation Abstract International |
| 대출바로가기 | http://www.riss.kr/pdu/ddodLink.do?id=T14999508 |
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| No. | 등록번호 | 청구기호 | 소장처 | 도서상태 | 반납예정일 | 예약 | 서비스 | 매체정보 |
|---|---|---|---|---|---|---|---|---|
| 1 | WE00025355 | DP 519 | 가야대학교/전자책서버(컴퓨터서버)/ | 대출불가(별치) |
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