ben@sep.stanford.edu, mcgrant@stanford.edu

## ABSTRACTConvex optimization is an optimization technique which maximizes efficiency by fully harnessing the convex nature of certain problems. Here we test a convex optimization solver on a least-squares formulations of the Dix equation. Convex optimization has many useful traits including the ability to set bounds on the solution which are explored here. As well, this example serves as a test for the feasibility of convex optimization for future, more expensive tomography problems. |

- Introduction
- Least-Squares Dix Equation
- Convex Optimization
- Real Data Examples
- Conclusions
- Acknowledgments
- REFERENCES
- About this document ...

1/16/2007