Computational Methods For Inverse Problems And Applications
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Computational Methods for Inverse Problems
Provides a basic understanding of both the underlying mathematics and the computational methods used to solve inverse problems.
Computational Methods for Inverse Problems and Applications
This book highlights recent trends in inverse problems and their integration with computer science, a field rapidly evolving yet underexplored mathematically. ICMDS 2024 aims to unite scientists to explore the latest in mathematics and its applications across various scientific disciplines. Key topics include inverse problems, partial differential equations, mathematical control, numerical analysis, and computer science. Our goal is to provide substantial mathematical insights and practical applications to bridge this gap. With its growing significance in media and industry, this event promises to attract a diverse audience and foster collaboration across scientific domains. The main contribution of this book is to give some sufficient mathematical content with expressive results and accurate applications. As a growing field, it is gaining a lot of attention both in media as well as in the industry world, which will attract the interest of readers from different scientist discipline.
Linear and Nonlinear Inverse Problems with Practical Applications
Inverse problems arise in practical applications whenever there is a need to interpret indirect measurements. This book explains how to identify ill-posed inverse problems arising in practice and gives a hands-on guide to designing computational solution methods for them, with related codes on an accompanying website. The guiding linear inversion examples are the problem of image deblurring, x-ray tomography, and backward parabolic problems, including heat transfer. A thorough treatment of electrical impedance tomography is used as the guiding nonlinear inversion example which combines the analytic-geometric research tradition and the regularization-based school of thought in a fruitful manner. This book is complete with exercises and project topics, making it ideal as a classroom textbook or self-study guide for graduate and advanced undergraduate students in mathematics, engineering or physics who wish to learn about computational inversion. It also acts as a useful guide for researchers who develop inversion techniques in high-tech industry.