In this paper, we investigate the exponential synchronization issue of coupling delayed switching complex dynamical networks via impulsive control. Basing on the Lyapunov functional method and establishing a new impulsive delay differential inequality, we derive some sufficient conditions which depend on delay and impulses to guarantee the exponential synchronization of the coupling delay switching complex dynamical network. Finally, numerical simulations are given to illustrate the effectiveness of the obtained results.

Constraint-based clustering utilizes pairwise constraints to improve clustering performance. In this paper, we propose a novel formulation algorithm to generate more informative pairwise constraints from limited queries for the constraint-based clustering. Our method consists of two phases: pre-clustering and marking. The pre-clustering phase introduces the fuzzy c-means clustering (FCM) to generate the cluster knowledge that is composed of the membership degree and the cluster centers. In the marking phase, we first propose the weak sample with the larger uncertainty expressed by the entropy of the membership degree. Then, we study the strong sample that contains less uncertainty and should be closest to its cluster center. Finally, given weak samples in descending order of entropy, we formulate informative pairs with strong samples and seek answers using the second minimal symmetric relative entropy priority principle, which leads to more efficient queries. Making use of the pairwise constraint k-means clustering (PCKM) as the underlying constraint-based clustering algorithm, further data experiments are conducted in several datasets to verify the improvement of our method.INDEX TERMS Constraint-based clustering, pairwise constraint, weak sample, strong sample, symmetric relative entropy.

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