Free Delivery Over $100
|
|
|||
|
||||
OverviewThis 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. Full Product DetailsAuthor: Kensuke Sekihara , Srikantan S. NagarajanPublisher: Springer International Publishing AG Imprint: Springer International Publishing AG Edition: 2015 ed. Dimensions: Width: 15.50cm , Height: 1.80cm , Length: 23.50cm Weight: 5.502kg ISBN: 9783319149462ISBN 10: 3319149466 Pages: 270 Publication Date: 20 March 2015 Audience: Professional and scholarly , Professional & Vocational Format: Hardback Publisher's Status: Active Availability: Manufactured on demand  We will order this item for you from a manufactured on demand supplier. Table of ContentsIntroduction 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.ReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |
||||
