@inproceedings {759,
	title = {Parameterized hierarchical annealing for scientific models},
	booktitle = {2004 International Conference on Image Analysis and Recognition},
	year = {2004},
	address = {Portugal},
	abstract = {<p>The accurate synthesis of binary porous media is a difficult problem. Initial applications of simulated annealing in this context with small data sets and simple energy functions have met with limited success. Simulated annealing has been applied to a wide variety of problems in image processing. Particularly in scientific applications such as discussed here, the computational complexity of this approach may constrain its effectiveness; complex, non-local models on large 2D and 3D domains may be desired, but do not lend themselves to traditional simulated annealing due to computational cost. These considerations naturally lead to a wish for hierarchical/multiscale methods. However, existing methods are few and limited. In this paper a method of hierarchical simulated annealing is discussed, and a simple parameterization proposed to address the problem of moving through the hierarchy. This approach shows significant gains in convergence and computational complexity when compared to the simulated annealing algorithm.</p>
},
	keywords = {dblp},
	isbn = {3-540-23240-0},
	url = {http://dblp.uni-trier.de/db/conf/iciar/iciar2004-1.html$\#$AlexanderFV04},
	author = {P Fieguth and S K. Alexander}
}
