| Paper: | IMDSP-L2.3 | ||
| Session: | Image and Multidimensional Signal Processing: Theory | ||
| Time: | Wednesday, May 19, 16:10 - 16:30 | ||
| Presentation: | Lecture | ||
| Topic: | Image and Multidimensional Signal Processing: Image Formation and Computed Imaging | ||
| Title: | HIERARCHICAL ANNEALING FOR SCIENTIFIC MODELS | ||
| Authors: | Simon Alexander; University of Waterloo | ||
| Edward Vrscay; University of Waterloo | |||
| Paul Fieguth; University of Waterloo | |||
| Abstract: | The computational complexity of simulated annealing makes it an impractical tool in many applications, particularly for complex, non-local models on very large 2D and 3D domains as desired in many scientific contexts. In particular, it is very difficult to produce large scale structure from a fine, pixellated lattice. Thus a hierarchical approach is intuitively attractive. However, existing approaches are few and limited. Motivated by a current problem in porous media, we develop a hierarchical approach to complex model sampling. In experiments, this approach results in 1--2 orders of magnitude computational gain, and significant gains in convergence as well. | ||
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