| 000 | 01507 a2200361 4500 | ||
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| 001 | 0367780283 | ||
| 005 | 20250317100417.0 | ||
| 008 | 250312042021xx eng | ||
| 020 | _a9780367780289 | ||
| 037 |
_bTaylor & Francis _cGBP 45.99 _fBB |
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| 040 | _a01 | ||
| 041 | _aeng | ||
| 072 | 7 |
_aTGM _2thema |
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_aPHFC _2thema |
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_aPB _2thema |
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_aPHFC _2bic |
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_aPB _2bic |
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_aSCI077000 _2bisac |
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_aMAT029000 _2bisac |
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_aSCI055000 _2bisac |
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| 072 | 7 |
_aTEC021000 _2bisac |
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| 072 | 7 |
_a620.110727 _2bisac |
|
| 100 | 1 | _aJeffrey P. Simmons | |
| 245 | 1 | 0 |
_aStatistical Methods for Materials Science _bThe Data Science of Microstructure Characterization |
| 250 | _a1 | ||
| 260 |
_bCRC Press _c20210331 |
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| 300 | _a514 p | ||
| 520 | _bData 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. | ||
| 700 | 1 |
_aLawrence F. Drummy _4B01 |
|
| 700 | 1 |
_aCharles A. Bouman _4B01 |
|
| 700 | 1 |
_aMarc De Graef _4B01 |
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| 999 |
_c3001 _d3001 |
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