| Review: |
Given a complete description of a physical system, we can predict the outcome of some measurements. The problem of predicting measurements is called the ‘modelization problem’, the ‘simulation problem’, or the ‘forward problem’. The ‘inverse problem’ consists of using the actual result of some measurements to infer the values of the parameters that characterize the system. Inverse problems are difficult because they do not have unique solutions. The approach is probabilistic, allowing the reader to understand the basic difficulties in resolving inverse problems. The first part of the book deals exclusively with discrete inverse problems that have a finite number of parameters. The second part looks at general inverse problems, which may contain functions such as data unknowns. |