Advances in Wireless Networks and Information Systems by Ming-hui Wu, Fan-wei Zhu (auth.), Qi Luo (eds.)

By Ming-hui Wu, Fan-wei Zhu (auth.), Qi Luo (eds.)

This quantity comprises revised and prolonged examine articles written by way of fashionable researchers engaging in WNIS 2009 convention. issues coated contain instant details Networks, instant Networking applied sciences, cellular software program and prone, clever computing, community administration, energy engineering, keep watch over engineering, sign and photo Processing, computer studying, regulate platforms and functions, The ebook will supply the states of arts of great advances in instant Networks and knowledge platforms and likewise function an exceptional reference paintings for researchers and graduate scholars engaged on instant Networks and data Systems.

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I =1 The consensus state of system (1) is affected by the initialized values of multiagent systems. If the initialized values are set at random, the consensus state can not be converged to an expected value. In this paper, we apply pinning control to bring the consensus state of multiple agents to an expected value. 3 Mobile Agent Systems with Pinning Control Suppose mobile agent systems are composed of n agents with directed connected topology and have a globally reachable node i. Now, we add a pinning control on the node i u = − k ( xi − α 0 ) , where control gain k>0, α0 (2) is the expected consensus state of multi-agent system.

Finally, computer simulations are used to show the validity of the result. Keywords: Mobile agent systems, wireless networks, consensus, pinning control, communication delays. 1 Introduction In recent years, there has been an increasing research interest in the control design of multi-agent systems. Many results have been obtained with local rules applied to each agent in a considered multi-agent system. For example, Jadbabaie et al. [1] demonstrated that a simple neighbor rule makes all agents eventually move in the same direction despite the absence of centralized coordination and each agent’s set of neighbors changing with times as the system evolves under a joint connection condition.

Combining local context and WordNet similarity for word sense identification. In: Christiane Fellbaum, pp. 265–283 (1998) 11. : Word similarity in WordNet. In: Proceedings of the Third International Conference on High Performance Scientific Computing, Hanoi, Vietnam, pp. 1–10 (March 2006) 12. : Disambiguating noun groupings with respect to WordNet senses. In: Third Workshop on Very Large Corpora, Cambridge. Association for Computational Linguistics, pp. 55–68 (1995) 13. : Using information content to evaluate semantic similarity in a taxonomy.

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