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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Data-Driven Computational Methods

Data-Driven Computational Methods

Harlim, John

Hardcover

General ComputersProbability & Statistics

ISBN10: 1108472478
ISBN13: 9781108472470
Publisher: Cambridge University Press
Published: Aug 30 2018
Pages: 168
Weight: 1.10
Height: 0.56 Width: 7.11 Depth: 9.98
Language: English
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(R) codes and appendices covering the relevant prerequisite materials are provided, making it suitable for self-study.

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