A tutorial

sergey@sep.stanford.edu

## ABSTRACTConstraining ill-posed inverse problems often requires regularized optimization. I describe two alternative approaches to regularization. The first approach involves a column operator and an extension of the data space. The second approach constructs a row operator and expands the model space. In large-scale problems, when the optimization is incomplete, the two methods of regularization behave differently. I illustrate this fact with simple examples and discuss its implications for geophysical problems. |

- Introduction
- Model-space regularization
- Data-space regularization
- Examples
- Stack equalization
- Discussion
- Acknowledgments
- REFERENCES
- Regularized Reusable Linear Solver
- About this document ...

11/11/1997