Daniel B. Rowe

Multivariate Bayesian Statistics (eBook, ePUB)

Models for Source Separation and Signal Unmixing

• Format: ePub

Produktbeschreibung

Of the two primary approaches to the classic source separation problem, only one does not impose potentially unreasonable model and likelihood constraints: the Bayesian statistical approach. Bayesian methods incorporate the available information regarding the model parameters and not only allow estimation of the sources and mixing coefficients, but

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Produktdetails

• Verlag: Taylor & Francis eBooks
• Seitenzahl: 352
• Erscheinungstermin: 25. November 2002
• Englisch
• ISBN-13: 9781000738186
• Artikelnr.: 57531000

Autorenporträt

Daniel B. Rowe holds a joint appointment as an assistant professor of Biophysics and Biostatistics at the Medical College of Wisconsin, Milwaukee, Wisconsin, USA.

Inhaltsangabe

FUNDAMENTALS: Statistical Distributions. Introductory Bayesian Statistics. Prior Distribution. Hyperparameter Assessment. Bayesian Estimation Methods. MODELS: Introduction. Bayesian Regression. Bayesian Factor Analysis. Bayesian Source Separation. Unobservable and Observable Sources. fMRI Case Study. GENERALIZATIONS: Delayed sources and Dynamic Coefficients. Correlated Observation and Source Vectors. fMRI Case Study. APPENDICES: Activation Determination. fMRI Hyperparameter Assessment.