Statistical Methods for Materials Science: The Data Science of Microstructure Characterization
Simmons, Jeffrey P. (Editor)/ Drummy, Lawrence F. (Editor)/ Bouman, Charles A. (Editor)/ De Graef, Marc (Editor)
ISBN 10: 0367780283 ISBN 13: 9780367780289
Published by CRC Pr I Llc, 2021
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536 pages. 10.00x7.01x1.26 inches. In Stock. This item is printed on demand. Seller Inventory # __0367780283
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Data analytics has become an integral part of materials science. This book provides the practical tools and fundamentals needed for researchers in materials science to understand how to analyze large datasets using statistical methods, especially inverse methods applied to microstructure characterization. It contains valuable guidance on essential topics such as denoising and data modeling. Additionally, the analysis and applications section addresses compressed sensing methods, stochastic models, extreme estimation, and approaches to pattern detection.
About the Author: Jeffrey P. Simmons, Lawrence F. Drummy, Charles A. Bouman, Marc De Graef
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Title: Statistical Methods for Materials Science: ...
Publisher: CRC Pr I Llc
Publication Date: 2021
Binding: Paperback
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Data analytics has become an integral part of materials science. This book provides the practical tools and fundamentals needed for researchers in materials science to understand how to analyze large datasets using statistical methods, especially inverse methods applied to microstructure characterization. It contains valuable guidance on essential topics such as denoising and data modeling. Additionally, the analysis and applications section addresses compressed sensing methods, stochastic models, extreme estimation, and approaches to pattern detection. Seller Inventory # 9780367780289
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Data analytics has become an integral part of materials science. This book provides the practical tools and fundamentals needed for researchers in materials science to understand how to analyze large datasets using statistical methods, especially inverse methods applied to microstructure characterization. It contains valuable guidance on essential topics such as denoising and data modeling. Additionally, the analysis and applications section addresses compressed sensing methods, stochastic models, extreme estimation, and approaches to pattern detection. 538 pp. Englisch. Seller Inventory # 9780367780289
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Statistical Methods for Materials Science: The Data Science of Microstructure Characterization
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