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<p>We prove the convergence of the simulated annealing procedure when the decision to change the current configuration is blind of the cost of the new configuration. In case of filtering binary images, the proof easily generalizes to other procedures, including that of Metropolis. We show that a function Q associated with the algorithm must be chosen as large as possible to provide a fast rate of convergence. The worst case (Q constant) is associated with the "blind" algorithm. On the other hand, an appropriate Q taking sufficiently high values yields a better rate of convergence than that of Metropolis procedure.</p>
simulated annealing; convergence; image processing; simulated annealing; convergence; binary image filtering; Metropolis procedure

V. Granville, M. Krivánek and J. Rasson, "Simulated Annealing: A Proof of Convergence," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 16, no. , pp. 652-656, 1994.
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