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231224s2013 xx |||||o 00| ||eng c |
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|a 10.1109/TIP.2012.2233482
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|a eng
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| 100 |
1 |
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|a Campaigne, Wesley R
|e verfasserin
|4 aut
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| 245 |
1 |
0 |
|a Frozen-state hierarchical annealing
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| 264 |
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|c 2013
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|a Text
|b txt
|2 rdacontent
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|a ƒaComputermedien
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|2 rdamedia
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|a ƒa Online-Ressource
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| 500 |
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|a Date Completed 22.07.2013
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|a Date Revised 12.02.2013
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|a published: Print-Electronic
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|a Citation Status PubMed-not-MEDLINE
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| 520 |
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|a There is significant interest in the synthesis of discrete-state random fields, particularly those possessing structure over a wide range of scales. However, given a model on some finest, pixellated scale, it is computationally very difficult to synthesize both large- and small-scale structures, motivating research into hierarchical methods. In this paper, we propose a frozen-state approach to hierarchical modeling, in which simulated annealing is performed on each scale, constrained by the state estimates at the parent scale. This approach leads to significant advantages in both modeling flexibility and computational complexity. In particular, a complex structure can be realized with very simple, local, scale-dependent models, and by constraining the domain to be annealed at finer scales to only the uncertain portions of coarser scales; the approach leads to huge improvements in computational complexity. Results are shown for a synthesis problem in porous media
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|a Journal Article
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|a Research Support, Non-U.S. Gov't
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| 700 |
1 |
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|a Fieguth, Paul W
|e verfasserin
|4 aut
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| 773 |
0 |
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|i Enthalten in
|t IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
|d 1992
|g 22(2013), 4 vom: 07. Apr., Seite 1486-97
|w (DE-627)NLM09821456X
|x 1941-0042
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|g volume:22
|g year:2013
|g number:4
|g day:07
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|g pages:1486-97
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|u http://dx.doi.org/10.1109/TIP.2012.2233482
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