یادداشتهای مربوط به کتابنامه ، واژه نامه و نمایه های داخل اثر
متن يادداشت
Includes bibliographical references (pages 151-155) and index.
یادداشتهای مربوط به مندرجات
متن يادداشت
Introduction -- Markov-Chain Monte Carlo -- Ensemble Kalman filters -- Stochastic spectral methods -- Karhunen-Loève expansion -- Diffusion forecast.
بدون عنوان
0
یادداشتهای مربوط به خلاصه یا چکیده
متن يادداشت
Modern scientific computational methods are undergoing a transformative change; big data and statistical learning methods now have the potential to outperform the classical first-principles modeling paradigm. This book bridges this transition, connecting the theory of probability, stochastic processes, functional analysis, numerical analysis, and differential geometry. It describes two classes of computational methods to leverage data for modeling dynamical systems. The first is concerned with data fitting algorithms to estimate parameters in parametric models that are postulated on the basis of physical or dynamical laws. The second is on operator estimation, which uses the data to nonparametrically approximate the operator generated by the transition function of the underlying dynamical systems. This self-contained book is suitable for graduate studies in applied mathematics, statistics, and engineering. Carefully chosen elementary examples with supplementary MATLAB® codes and appendices covering the relevant prerequisite materials are provided, making it suitable for self-study.
ویراست دیگر از اثر در قالب دیگر رسانه
عنوان
DATA-DRIVEN COMPUTATIONAL METHODS.
شماره استاندارد بين المللي کتاب و موسيقي
1108472478
عنوان به منزله موضوع
موضوع مستند نشده
Computational sciences.
رده بندی ديویی
شماره
519
.
22
ويراست
23
رده بندی کنگره
شماره رده
QA274
.
2
نشانه اثر
.
H37
2018
نام شخص به منزله سر شناسه - (مسئولیت معنوی درجه اول )