Parameter Estimation and Inverse Problems

Parameter Estimation and Inverse Problems

Aster, Richard C.
Borchers, Brian
Thurber, Clifford H.

74,83 €(IVA inc.)

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 may not have an extensive mathematical background. The book is complemented by a companion web site that includes Matlab codes which correspond to all examples. All examples in the book are illustrated with simple, easy to follow problems, and are designed to illuminate the details of a particular numerical method. Updates to the new edition include: more discussion of Laplacian smoothing in Chapter 4, expansion of basis function exercises in Chapter 5, addition of stochastic descent in Chapter 6, expansion of 1-­-norm solution methods and expansion of compressive sensing in Chapter 7, improved presentation of Fourier methods and exercises in Chapter 8, more examples and exercises in Chapter 9, introduction of basic adjoint methods using simple examples, and reduction of elementary material in the Appendices. Complemented by a companion web site that includes Matlab codes which correspond to all examplesFeatures examples throughout the book which are illustrated with simple, easy to follow problems, and are designed to illuminate the details of a particular numerical methodOnline instructor's guide helps professors teach, customize exercises, and select homework problemsIncludes updated information on adjoint methods, presented in an accessible manner. This method has become a rapidly emerging and very promising element of seismic and other inverse methodologies as forward modelling capabilities have increased INDICE: 1. Introduction 2. Linear Regression 3. Rank Deficiency and Ill-­-Conditioning 4. Tikhonov Regularization 5. Discretizing by Basis Functions 6. Iterative Methods of Solving Linear Problems 7. Additional Regularization Techniques 8. Fourier Techniques 9. Nonlinear Regression 10. Nonlinear Inverse Problems 11. Bayesian Methods 12 Adjoint Methods

  • ISBN: 978-0-12-804651-7
  • Editorial: Elsevier
  • Encuadernacion: Rústica
  • Páginas: 400
  • Fecha Publicación: 01/08/2018
  • Nº Volúmenes: 1
  • Idioma: Inglés