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Statistical Methods for Materials Science: The Data Science of Microstructure Characterization

Editat de Jeffrey P. Simmons, Lawrence F. Drummy, Charles A. Bouman, Marc de Graef
en Limba Engleză Hardback – 6 feb 2019
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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Specificații

ISBN-13: 9781498738200
ISBN-10: 1498738206
Pagini: 536
Ilustrații: 19 Tables, black and white; 215 Illustrations, black and white
Dimensiuni: 178 x 254 x 34 mm
Greutate: 1.09 kg
Ediția:1
Editura: CRC Press
Colecția CRC Press

Cuprins

1 Materials Science vs. Data Science 2 Emerging Digital Data Capabilities 3 Cultural Differences 4 Forward Modeling 5 Inverse Problems and Sensing 6 Model-Based Iterative Reconstruction for Electron Tomography 7 Statistical reconstruction and heterogeneity characterization in 3-D biological macromolecular complexes  8 Object Tracking through Image Sequences 9 Grain Boundary Characteristics 10 Interface Science and the Formation of Structure 11 Hierarchical Assembled Structures from Nanoparticles  12 Estimating Orientation Statistics 13 Representation of Stochastic Microstructures 14  Computer Vision for Microstructure Representation 15 Topological Analysis of Local Structure  16 Markov Random Fields for Microstructure Simulation 17 Distance Measures for Microstructures  18 Industrial Applications  19 Anomaly Testing  20 Anomalies in Microstructures 21 Denoising Methods with Applications to Microscopy  22 Compressed Sensing for Imaging Applications 23 Dictionary Methods for Compressed Sensing 24 Sparse Sampling in Microscopy
 
 

Notă biografică

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

Descriere

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.