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eBook - ePub
Statistical Methods for Materials Science
The Data Science of Microstructure Characterization
Jeffrey P. Simmons, Lawrence F. Drummy, Charles A. Bouman, Marc De Graef, Jeffrey P. Simmons, Lawrence F. Drummy, Charles A. Bouman, Marc De Graef
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- 514 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
eBook - ePub
Statistical Methods for Materials Science
The Data Science of Microstructure Characterization
Jeffrey P. Simmons, Lawrence F. Drummy, Charles A. Bouman, Marc De Graef, Jeffrey P. Simmons, Lawrence F. Drummy, Charles A. Bouman, Marc De Graef
Book details
Table of contents
Citations
About This Book
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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Yes, you can access Statistical Methods for Materials Science by Jeffrey P. Simmons, Lawrence F. Drummy, Charles A. Bouman, Marc De Graef, Jeffrey P. Simmons, Lawrence F. Drummy, Charles A. Bouman, Marc De Graef in PDF and/or ePUB format, as well as other popular books in Physical Sciences & Condensed Matter. We have over one million books available in our catalogue for you to explore.
Information
Table of contents
- Cover
- Half Title
- Title Page
- Copyright Page
- Dedication
- Table of Contents
- Preface
- About the Editors
- Contributors
- I Introduction
- II Emerging Data Science in Microstructure Characterization
- III Inverse Methods for Analysis of Data
- IV Structure Formation in Materials
- V Microstructure
- VI Anomalies
- VII Sparse Methods
- Appendix A List of Symbols for Chapters 6, 7, and 13 440
- Bibliography
- Index