Parameter estimation and inverse problems

By:

Aster, Richard C

Contributor(s):

Material type: Text

TextPublication details: Amsterdam : Academic Press, 2019.Edition: 3rd editionDescription: xi, 392 pages : illustrations ; 24 cmISBN:

9780128046517

Subject(s):

DDC classification:

517.972.7 AST-P

Online resources:

Summary: Parameter Estimation and Inverse Problems, Third Edition, is structured around a course at New Mexico Tech and is designed to be accessible to typical graduate students in the physical sciences who do not have an extensive mathematical background. The book is complemented by a companion website that includes MATLAB codes that correspond to examples that are illustrated with simple, easy to follow problems that illuminate the details of particular numerical methods. Updates to the new edition include more discussions of Laplacian smoothing, an expansion of basis function exercises, the addition of stochastic descent, an improved presentation of Fourier methods and exercises, and more.

List(s) this item appears in: Mathematics

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Item type	Current library	Call number	Status	Barcode
Book	NISER LIBRARY	517.972.7 AST-P (Browse shelf(Opens below))	Available	26455
Book	NISER LIBRARY	517.972.7 AST-P (Browse shelf(Opens below))	Available	24301
Book	NISER LIBRARY	517.972.7 AST-P (Browse shelf(Opens below))	R (REFERENCE)	21673

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Previous	517.972 GHO-C Course in multivariable calculus and analysis(a)	517.972.7 AST-P Parameter estimation and inverse problems	517.972.7 AST-P Parameter estimation and inverse problems	517.972.7 AST-P Parameter estimation and inverse problems	517.972.7 MEH-I Inverse problems and tikhonov regularization	517.972.7 SAN-I Inverse problems and data assimilation	517.972.7 TEN-I Introduction to data analysis and uncertainty quantification for inverse problems (an)	Next

Includes bibliographical references (pages 373-381) and index.

Parameter Estimation and Inverse Problems, Third Edition, is structured around a course at New Mexico Tech and is designed to be accessible to typical graduate students in the physical sciences who do not have an extensive mathematical background. The book is complemented by a companion website that includes MATLAB codes that correspond to examples that are illustrated with simple, easy to follow problems that illuminate the details of particular numerical methods. Updates to the new edition include more discussions of Laplacian smoothing, an expansion of basis function exercises, the addition of stochastic descent, an improved presentation of Fourier methods and exercises, and more.

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