A saturated linear dynamical network for approximating maximum clique
IEEE Transactions Circuits and Systems I Fundamental theory and applications
677 - 685
MetadataShow full item record
Pekergin, F., Morgui, O., & Güzeliş, C. (1999). A saturated linear dynamical network for approximating maximum clique. Circuits and Systems I: Fundamental Theory and Applications, IEEE Transactions on, 46(6), 677-685.
Please cite this item using this persistent URLhttp://hdl.handle.net/11693/10911
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.