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Statistical Methods for Materials Science: The Data Science of Microstructure Characterization - Rilegato
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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.
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Jeffrey P. Simmons, Lawrence F. Drummy, Charles A. Bouman, Marc De Graef
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Statistical Methods for Materials Science
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Gebunden. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Jeffrey P. Simmons is a Scientist with the Materials and Manufacturing Directorate of the Air Force Research Laboratory (AFRL). He received the B.S. degree in metallurgical engineering from the New Mexico Institute of Mining and Technolo. Codice articolo 596130600
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Statistical Methods for Materials Science: The Data Science of Microstructure Characterization
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Statistical Methods for Materials Science (Hardcover)
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Hardcover. Condizione: new. Hardcover. 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. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Codice articolo 9781498738200
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Statistical Methods for Materials Science (Hardcover)
Editore:
Taylor & Francis Inc, Bosa Roca, 2019
ISBN 10: 1498738206
ISBN 13: 9781498738200
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Hardcover. Condizione: new. Hardcover. 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. 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. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Codice articolo 9781498738200
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