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(c) 2000-2002 SNU CSE Biointelligence Lab, http://bi.snu.ac.kr Ch 6.14-6.15 Joon Shik Kim BI study, 09.07.17 (c) 2000-2002 SNU CSE Biointelligence Lab, http://bi.snu.ac.kr

(c) 2000-2002 SNU CSE Biointelligence Lab, http://bi.snu.ac.kr 6.14 EFFECTIVE POTENTIALS Statistical mechanics of the Markov random field formalism can be used to generate effective potentials of te graduated nonconvexity form (c) 2000-2002 SNU CSE Biointelligence Lab, http://bi.snu.ac.kr

(c) 2000-2002 SNU CSE Biointelligence Lab, http://bi.snu.ac.kr

(c) 2000-2002 SNU CSE Biointelligence Lab, http://bi.snu.ac.kr

6.15 RENORMALIZATION GROUP SIMULATED ANNEALING Basic idea of the renormalization group approach is to combine local processing of information at different length scales, the RG cascade, with an interscale transfer of information, the RG transformation. The Gidas renormalization group algorithm is a procedure for global optimization that generates iteratively a cascade of restored images corresponding to different levels of resolution. (c) 2000-2002 SNU CSE Biointelligence Lab, http://bi.snu.ac.kr

6.15.1 Kadanoff Transformation t is the new spin configuration and s is the old spin array (c) 2000-2002 SNU CSE Biointelligence Lab, http://bi.snu.ac.kr

(c) 2000-2002 SNU CSE Biointelligence Lab, http://bi.snu.ac.kr 6.15.2 The Gidas Algorithm (c) 2000-2002 SNU CSE Biointelligence Lab, http://bi.snu.ac.kr

(c) 2000-2002 SNU CSE Biointelligence Lab, http://bi.snu.ac.kr Ising lattice (c) 2000-2002 SNU CSE Biointelligence Lab, http://bi.snu.ac.kr

(c) 2000-2002 SNU CSE Biointelligence Lab, http://bi.snu.ac.kr