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Data-Driven Computational Methods, Harlim John


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Цена: 9029.00р.
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При оформлении заказа до: 2025-08-04
Ориентировочная дата поставки: Август-начало Сентября
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Автор: Harlim John
Название:  Data-Driven Computational Methods
ISBN: 9781108472470
Издательство: Cambridge Academ
Классификация:
ISBN-10: 1108472478
Обложка/Формат: Hardback
Страницы: 168
Вес: 0.53 кг.
Дата издания: 12.07.2018
Серия: Mathematics
Язык: English
Иллюстрации: Worked examples or exercises; 00 printed music items; 00 tables, unspecified; 00 tables, color; 00 tables, black and white; 00 plates, unspecified; 00 plates, color; 00 plates, black and white; 00 maps; 00 halftones, unspecified; 7 halftones, color;
Размер: 180 x 253 x 10
Читательская аудитория: Tertiary education (us: college)
Ключевые слова: Probability & statistics,Mathematical modelling,Astrophysics,Atmospheric physics,Mathematical theory of computation, COMPUTERS / General
Подзаголовок: Parameter and operator estimations
Ссылка на Издательство: Link
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Поставляется из: Англии
Описание: The mathematics behind, and the practice of, computational methods that leverage data for modelling dynamical systems are described in this book. It will teach readers how to fit data on the assumed model and how to use data to determine the underlying model. Suitable for graduate students in applied mathematics, statistics, and engineering.


Methods in Molecular Biophysics: Structure, Dynamics, Function for Biology and Medicine, 2 ed.

Автор: Zaccai, Nathan R. (University of Cambridge) Serdyuk, Igor N. Zaccai, Joseph
Название: Methods in Molecular Biophysics: Structure, Dynamics, Function for Biology and Medicine, 2 ed.
ISBN: 1107056373 ISBN-13(EAN): 9781107056374
Издательство: Cambridge Academ
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Цена: 9029.00 р.
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Описание: Reflecting the significant developments of the past decade, this textbook explains key physical methods in modern biology. Each method is illustrated through real-world examples, alongside background information designed for both physicists and biologists, making this an ideal resource for students in biophysics at science and medical schools.

Computational complexity

Автор: Arora, Sanjeev Barak, Boaz
Название: Computational complexity
ISBN: 0521424267 ISBN-13(EAN): 9780521424264
Издательство: Cambridge Academ
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Цена: 9029.00 р.
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Описание: Describes recent achievements and classical results of computational complexity theory, including interactive proofs, PCP, derandomization, and quantum computation. It can be used as a reference, for self-study, or as a beginning graduate textbook. More than 300 exercises are included.

Computational and Statistical Methods for Analysing Big Data with

Автор: Shen Liu
Название: Computational and Statistical Methods for Analysing Big Data with
ISBN: 0128037326 ISBN-13(EAN): 9780128037324
Издательство: Elsevier Science
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Цена: 11620.00 р.
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Описание:

Due to the scale and complexity of data sets currently being collected in areas such as health, transportation, environmental science, engineering, information technology, business and finance, modern quantitative analysts are seeking improved and appropriate computational and statistical methods to explore, model and draw inferences from big data. This book aims to introduce suitable approaches for such endeavours, providing applications and case studies for the purpose of demonstration.

"Computational and Statistical Methods for Analysing Big Data with Applications" starts with an overview of the era of big data. It then goes onto explain the computational and statistical methods which have been commonly applied in the big data revolution. For each of these methods, an example is provided as a guide to its application. Five case studies are presented next, focusing on computer vision with massive training data, spatial data analysis, advanced experimental design methods for big data, big data in clinical medicine, and analysing data collected from mobile devices, respectively. The book concludes with some final thoughts and suggested areas for future research in big data.

Advanced computational and statistical methodologies for analysing big data are developed.

Experimental design methodologies are described and implemented to make the analysis of big data more computationally tractable.

Case studies are discussed to demonstrate the implementation of the developed methods.

Five high-impact areas of application are studied: computer vision, geosciences, commerce, healthcare and transportation.

Computing code/programs are provided where appropriate.

Advances in Complex Data Modeling and Computational Methods in Statistics

Автор: Anna Maria Paganoni; Piercesare Secchi
Название: Advances in Complex Data Modeling and Computational Methods in Statistics
ISBN: 3319385372 ISBN-13(EAN): 9783319385372
Издательство: Springer
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Цена: 9781.00 р.
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Описание: The book is addressed to statisticians working at the forefront of the statistical analysis of complex and high dimensional data and offers a wide variety of statistical models, computer intensive methods and applications: network inference from the analysis of high dimensional data;

Recent Advances in Computational Methods and Clinical Applications for Spine Imaging

Автор: Jianhua Yao; Ben Glocker; Tobias Klinder; Shuo Li
Название: Recent Advances in Computational Methods and Clinical Applications for Spine Imaging
ISBN: 3319385992 ISBN-13(EAN): 9783319385990
Издательство: Springer
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Цена: 14365.00 р.
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Описание: This book contains the full papers presented at the MICCAI 2014 workshop on Computational Methods and Clinical Applications for Spine Imaging. The workshop brought together scientists and clinicians in the field of computational spine imaging. The chapters included in this book present and discuss the new advances and challenges in these fields, using several methods and techniques in order to address more efficiently different and timely applications involving signal and image acquisition, image processing and analysis, image segmentation, image registration and fusion, computer simulation, image based modeling, simulation and surgical planning, image guided robot assisted surgical and image based diagnosis.

The book also includes papers and reports from the first challenge on vertebra segmentation held at the workshop.

Basic elements of computational statistics

Автор: Hardle, Wolfgang Karl Okhrin, Yarema Okhrin, Ostap
Название: Basic elements of computational statistics
ISBN: 3319553356 ISBN-13(EAN): 9783319553351
Издательство: Springer
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Цена: 9362.00 р.
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Описание: This textbook on computational statistics presents tools and concepts of univariate and multivariate statistical data analysis with a strong focus on applications and implementations in the statistical software R.

Computational Methods in Geophysical Electromagnetics

Автор: Haber
Название: Computational Methods in Geophysical Electromagnetics
ISBN: 1611973791 ISBN-13(EAN): 9781611973792
Издательство: Mare Nostrum (Eurospan)
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Цена: 10395.00 р.
Наличие на складе: Нет в наличии.

Описание: Bridging the gap between theory and applications, this monograph provides a framework for the solution of electromagnetic imaging problems in geophysics. It provides a simple explanation of finite volume discretization; a full description of the basic concepts for solving inverse problems through optimization; a summary of applied electromagnetics methods; and MATLAB® code for efficient computation. The book will appeal to students and practitioners interested in computational science, data fitting, and applications to electromagnetics.

Computational Methods for Inverse Problems

Автор: Vogel Curtis R
Название: Computational Methods for Inverse Problems
ISBN: 0898715504 ISBN-13(EAN): 9780898715507
Издательство: Mare Nostrum (Eurospan)
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Цена: 10534.00 р.
Наличие на складе: Нет в наличии.

Описание: Inverse problems arise in a number of important practical applications, ranging from biomedical imaging to seismic prospecting. This book provides the reader with a basic understanding of both the underlying mathematics and the computational methods used to solve inverse problems. It also addresses specialized topics like image reconstruction, parameter identification, total variation methods, nonnegativity constraints, and regularization parameter selection methods. Because inverse problems typically involve the estimation of certain quantities based on indirect measurements, the estimation process is often ill-posed. Regularization methods, which have been developed to deal with this ill-posedness, are carefully explained in the early chapters of Computational Methods for Inverse Problems. The book also integrates mathematical and statistical theory with applications and practical computational methods, including topics like maximum likelihood estimation and Bayesian estimation.


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