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A saturated linear dynamical network for approximating maximum clique

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3 Author(s)
F. Pekergin ; Lab. d'Inf., Univ. de Paris-Nord, Villetaneuse, France ; O. Morgui ; C. Guzelis

We use a saturated linear gradient dynamical network for finding an approximate solution to the maximum clique problem. We show that for almost all initial conditions, any solution of the network defined on a closed hypercube reaches one of the vertices of the hypercube, and any such vertex corresponds to a maximal clique. We examine the performance of the method on a set of random graphs and compare the results with those of some existing methods. The proposed model presents a simple continuous, yet powerful, solution in approximating maximum clique, which may outperform many relatively complex methods, e.g., Hopfield-type neural network based methods and conventional heuristics

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IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications  (Volume:46 ,  Issue: 6 )