Verlag: World Scientific Pub Co Inc, 2012
ISBN 10: 9814335436 ISBN 13: 9789814335430
Sprache: Englisch
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Verlag: World Scientific Pub Co Inc, 2012
ISBN 10: 9814335436 ISBN 13: 9789814335430
Sprache: Englisch
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Verlag: World Scientific Pub Co Inc, 2012
ISBN 10: 9814335436 ISBN 13: 9789814335430
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Verlag: World Scientific Pub Co Inc, 2012
ISBN 10: 9814335436 ISBN 13: 9789814335430
Sprache: Englisch
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Verlag: World Scientific Publishing Company, Incorporated, 2012
ISBN 10: 9814335436 ISBN 13: 9789814335430
Sprache: Englisch
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Verlag: World Scientific Pub Co Inc, 2012
ISBN 10: 9814335436 ISBN 13: 9789814335430
Sprache: Englisch
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ISBN 10: 9814335436 ISBN 13: 9789814335430
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ISBN 10: 9814335436 ISBN 13: 9789814335430
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Verlag: Cambridge University Press, Cambridge, 2019
ISBN 10: 110718486X ISBN 13: 9781107184862
Sprache: Englisch
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Hardcover. Zustand: new. Hardcover. This tutorial reference serves as a coherent overview of various statistical and mathematical approaches used in brain network analysis, where modeling the complex structures and functions of the human brain often poses many unique computational and statistical challenges. This book fills a gap as a textbook for graduate students while simultaneously articulating important and technically challenging topics. Whereas most available books are graph theory-centric, this text introduces techniques arising from graph theory and expands to include other different models in its discussion on network science, regression, and algebraic topology. Links are included to the sample data and codes used in generating the book's results and figures, helping to empower methodological understanding in a manner immediately usable to both researchers and students. This tutorial reference provides a coherent overview of statistical and mathematical approaches used in brain network analysis. It goes beyond graph theory to explore different models in network science, regression, and algebraic topology, empowering methodological understanding in a manner immediately usable to both researchers and students. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Verlag: Cambridge University Press, 2019
ISBN 10: 110718486X ISBN 13: 9781107184862
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ISBN 10: 110718486X ISBN 13: 9781107184862
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Verlag: Cambridge University Press, 2019
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In den WarenkorbHardcover. Zustand: new. Hardcover. This tutorial reference serves as a coherent overview of various statistical and mathematical approaches used in brain network analysis, where modeling the complex structures and functions of the human brain often poses many unique computational and statistical challenges. This book fills a gap as a textbook for graduate students while simultaneously articulating important and technically challenging topics. Whereas most available books are graph theory-centric, this text introduces techniques arising from graph theory and expands to include other different models in its discussion on network science, regression, and algebraic topology. Links are included to the sample data and codes used in generating the book's results and figures, helping to empower methodological understanding in a manner immediately usable to both researchers and students. This tutorial reference provides a coherent overview of statistical and mathematical approaches used in brain network analysis. It goes beyond graph theory to explore different models in network science, regression, and algebraic topology, empowering methodological understanding in a manner immediately usable to both researchers and students. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Taschenbuch. Zustand: Neu. Neuware - The massive amount of nonstandard high-dimensional brain imaging data being generated is often difficult to analyze using current techniques. This challenge in brain image analysis requires new computational approaches and solutions. Unfortunately, few research papers or books in the field describe the quantitative techniques with detailed illus.
Verlag: Cambridge University Press, Cambridge, 2019
ISBN 10: 110718486X ISBN 13: 9781107184862
Sprache: Englisch
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Hardcover. Zustand: new. Hardcover. This tutorial reference serves as a coherent overview of various statistical and mathematical approaches used in brain network analysis, where modeling the complex structures and functions of the human brain often poses many unique computational and statistical challenges. This book fills a gap as a textbook for graduate students while simultaneously articulating important and technically challenging topics. Whereas most available books are graph theory-centric, this text introduces techniques arising from graph theory and expands to include other different models in its discussion on network science, regression, and algebraic topology. Links are included to the sample data and codes used in generating the book's results and figures, helping to empower methodological understanding in a manner immediately usable to both researchers and students. This tutorial reference provides a coherent overview of statistical and mathematical approaches used in brain network analysis. It goes beyond graph theory to explore different models in network science, regression, and algebraic topology, empowering methodological understanding in a manner immediately usable to both researchers and students. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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