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.

Bestandsnummer des Verk�ufers 9781498738200

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Bibliografische Details

Titel

Statistical Methods for Materials Science (Hardcover)

Verlag

Taylor & Francis Inc, Bosa Roca

Erscheinungsjahr

2019

Sprache

Englisch

ISBN-10

1498738206

ISBN-13

9781498738200

Einband

Hardcover

Zustand

new

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Inhaltsangabe

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.

�ber die Autorin bzw. den Autor

Jeffrey P. Simmons, Lawrence F. Drummy, Charles A. Bouman, Marc De Graef

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