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Parameter estimation and inverse problems

By: Contributor(s): Material type: TextTextPublication 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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Holdings
Item type Current library Call number Status Barcode
Book Book NISER LIBRARY 517.972.7 AST-P (Browse shelf(Opens below)) Available 26455
Book Book NISER LIBRARY 517.972.7 AST-P (Browse shelf(Opens below)) Available 24301
Book Book NISER LIBRARY 517.972.7 AST-P (Browse shelf(Opens below)) R (REFERENCE) 21673

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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