Parameter Estimation And Inverse Problems 3rd Ed Aster Richard C Borchers by Aster, Richard C.; Borchers, Brian; Thurber, Clifford H 9780128046517, 0128046511 instant download after payment.

Our principal goal for this text continues to be introductory to intermediate level philosophical and methodological understanding of parameter estimation and inverse problems, specifically regarding such key issues as uncertainty, ill-posedness, regularization, bias, and resolution. The accompanying exercises include a mix of applied and theoretical problems. We emphasize key theoretical points and applications with illustrative examples. MATLAB codes and associated data that implement these examples are available in a GitHub repository at https://github.com/brianborchers/PEIP. We welcome questions, comments, and suggested improvements to the code. The margin icon shown here also indicates where associated code and/or data associated with exercises are available in the repository. This book has necessarily had to distill a tremendous body of mathematics going back to (at least) Newton and Gauss. We hope that it will continue to find a broad audience of students and professionals interested in the general problem of estimating physical models from data. Because this is an introductory text surveying a very broad field, we have not been able to go into great depth. However, each chapter has a “notes and further reading” section to help guide the reader to further exploration of specific topics.