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Electromagnetic brain imaging [electronic resource] : a bayesian perspe

Electromagnetic brain imaging [electronic resource] : a bayesian perspe

자료유형
E-Book(소장)
개인저자
Sekihara, Kensuke. Nagarajan, Srikantan S.
서명 / 저자사항
Electromagnetic brain imaging [electronic resource] : a bayesian perspe / Kensuke Sekihara, Srikantan S. Nagarajan.
발행사항
Cham :   Springer International Publishing :   Imprint: Springer,   2015.  
형태사항
1 online resource (xiv, 270 p.) : ill. (some col.).
ISBN
9783319149479
요약
This graduate level textbook provides a coherent introduction to the body of main-stream algorithms used in electromagnetic brain imaging, with specific emphasis on novel Bayesian algorithms.  It helps readers to more easily understand literature in biomedical engineering and related fields, and be ready to pursue research in either the engineering or the neuroscientific aspects of electromagnetic brain imaging.  This textbook will not only appeal to graduate students but all scientists and engineers engaged in research on electromagnetic brain imaging.
일반주기
Title from e-Book title page.  
내용주기
Introduction to Electromagnetic Brain Imaging -- Minimum-Norm-Based Source Imaging Algorithms -- Adaptive Beamformers -- Sparse Bayesian (Champagne) Algorithm -- Bayesian Factor Analysis: A Versatile Framework -- A Unified Bayesian Framework for MEG/EEG Source -- Source-Space Connectivity Analysis Using Imaginary -- Estimation of Causal Networks: Source-Space Causality Analysis -- Detection of Phase–Amplitude Coupling in MEG Source Space: An Empirical Study.
서지주기
Includes bibliographical references and index.
이용가능한 다른형태자료
Issued also as a book.  
일반주제명
Medicine. Magnetoencephalography --Mathematical models. Magnetoencephalography --Data processing.
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100 1 ▼a Sekihara, Kensuke.
245 1 0 ▼a Electromagnetic brain imaging ▼h [electronic resource] : ▼b a bayesian perspe / ▼c Kensuke Sekihara, Srikantan S. Nagarajan.
260 ▼a Cham : ▼b Springer International Publishing : ▼b Imprint: Springer, ▼c 2015.
300 ▼a 1 online resource (xiv, 270 p.) : ▼b ill. (some col.).
500 ▼a Title from e-Book title page.
504 ▼a Includes bibliographical references and index.
505 0 ▼a Introduction to Electromagnetic Brain Imaging -- Minimum-Norm-Based Source Imaging Algorithms -- Adaptive Beamformers -- Sparse Bayesian (Champagne) Algorithm -- Bayesian Factor Analysis: A Versatile Framework -- A Unified Bayesian Framework for MEG/EEG Source -- Source-Space Connectivity Analysis Using Imaginary -- Estimation of Causal Networks: Source-Space Causality Analysis -- Detection of Phase–Amplitude Coupling in MEG Source Space: An Empirical Study.
520 ▼a This graduate level textbook provides a coherent introduction to the body of main-stream algorithms used in electromagnetic brain imaging, with specific emphasis on novel Bayesian algorithms.  It helps readers to more easily understand literature in biomedical engineering and related fields, and be ready to pursue research in either the engineering or the neuroscientific aspects of electromagnetic brain imaging.  This textbook will not only appeal to graduate students but all scientists and engineers engaged in research on electromagnetic brain imaging.
530 ▼a Issued also as a book.
538 ▼a Mode of access: World Wide Web.
650 0 ▼a Medicine.
650 0 ▼a Magnetoencephalography ▼x Mathematical models.
650 0 ▼a Magnetoencephalography ▼x Data processing.
700 1 ▼a Nagarajan, Srikantan S.
856 4 0 ▼u https://oca.korea.ac.kr/link.n2s?url=http://dx.doi.org/10.1007/978-3-319-14947-9
945 ▼a KLPA
991 ▼a E-Book(소장)

소장정보

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No. 1 소장처 중앙도서관/e-Book 컬렉션/ 청구기호 CR 616.8047547 등록번호 E14026919 도서상태 대출불가(열람가능) 반납예정일 예약 서비스 M

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