Statistical methods for materials science : the data science of microstructure characterization / edited by Jeffrey P. Simmons, Charles A. Bouman, Marc De Graef, Lawrence F. Drummy, Jr.
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 characteriz...
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| Online Access: |
Full Text (via Taylor & Francis) |
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| Other Authors: | , , , |
| Format: | eBook |
| Language: | English |
| Published: |
Boca Raton, Florida :
CRC Press,
[2019]
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| Subjects: |
| Summary: | 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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| Physical Description: | 1 online resource. |
| Bibliography: | Includes bibliographical references and index. |
| ISBN: | 9781351647380 1351647385 9781315121062 1315121069 9781351637879 1351637878 9781498738217 1498738214 |