Browsing by Subject "Saturated linear gradient dynamical network"

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    A saturated linear dynamical network for approximating maximum clique
    (Institute of Electrical and Electronics Engineers, 1999-06) Pekergin, F.; Morgül, Ö.; Güzeliş, C.
    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.