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Statistical Methods for Materials Science

Statistical Methods for Materials Science

Autorzy
Wydawnictwo Productivity Press Inc
Data wydania 01/02/2019
Wydanie Pierwsze
Liczba stron 514
Forma publikacji książka w twardej oprawie
Poziom zaawansowania Dla szkół wyższych i kształcenia podyplomowego
Język angielski
ISBN 9781498738200
Kategorie Prawdopodobieństwo i statystyka, Fizyka ciał skondensowanych (fizyka ciał ciekłych i fizyka ciał stałych), Nauka o materiałach
1 246.11 PLN (z VAT)
$314.51 / €291.22 / £243.80 /
Produkt na zamówienie
Dostawa 5-6 tygodni
Ilość
Do schowka

Opis książki

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.

Statistical Methods for Materials Science

Spis treści

Chapter 1 Materials Science vs. Data Science


Jeff Simmons, Lawrence Drummy, Charles Bouman, Marc De Graef


Chapter 2 Emerging Digital Data Capabilities


Stephen Mick


Chapter 3 Cultural Differences


Mary Comer, Charles Bouman, Jeff Simmons


Chapter 4 Forward Modeling


Marc De Graef


Chapter 5 Inverse Problems and Sensing


Charles Bouman


Chapter 6 Model-Based Iterative Reconstruction for Electron Tomography


Singanallur Venkatakrishnan, Lawrence Drummy


Chapter 7 Statistical reconstruction and heterogeneity characterization in 3-D biological macromolecular complexes


Qiu Wang, Peter C. Doerschuk


Chapter 8 Object Tracking through Image Sequences


Song Wang, Hongkai Yu, Youjie Zhou, Jeff Simmons, Craig Przybyla


Chapter 9 Grain Boundary Characteristics


Hossein Beladi, Gregory S. Rohrer


Chapter 10 Interface Science and the Formation of Structure


Ming Tang, Jian Luo


Chapter 11 Hierarchical Assembled Structures from Nanoparticles


Dhriti Nepal, Sushil Kanel, Lawrence Drummy


Chapter 12 Estimating Orientation Statistics


Stephen R. Niezgoda


Chapter 13 Representation of Stochastic Microstructures


Stephen R. Niezgoda


Chapter 14 Computer Vision for Microstructure Representation


Brian DeCost, Elizabeth Holm


Chapter 15 Topological Analysis of Local Structure


Emanuel Lazar, David Srolovitz


Chapter 16 Markov Random Fields for Microstructure Simulation


Veera Sundararaghavan


Chapter 17 Distance Measures for Microstructures


Patrick Callahan


Chapter 18 Industrial Applications


David Furrer, David Brough, Ryan Noraas


Chapter 19 Anomaly Testing


James Theiler


Chapter 20 Anomalies in Microstructures


Stephen Bricker, Craig Przybyla, Jeff Simmons, Russel Hardie


Chapter 21 Denoising Methods with Applications to Microscopy


Rebecca Willett


Chapter 22 Compressed Sensing for Imaging Applications


Justin Romberg


Chapter 23 Dictionary Methods for Compressed Sensing


Saiprasad Ravishankar, Raj Rao Nadakuditi


Chapter 24 Sparse Sampling in Microscopy


Kurt Larson, Hyrum Anderson, Jason Wheeler

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