Abstract
Recently, much attention has been paid to the geometry features, synchronization and control of complex network associated with certain network structure. In this paper, by using Lyapunov theory, an adaptive feedback controlling scheme is proposed to identify the exact topology of a general weighted complex dynamical network model. By receiving the network nodes evolution, the topology of such kind of network with identical or different nodes, or even with switching topology can be monitored. Numerical simulation show that the methods presented in this paper are of high accuracy with good performance.
This work is by the Jiangsu Province Natural Science Foundations of University (No: 10KJD110002) and the Outstanding Personnel Program in Six Fields of Jiangsu (No: 2009188).
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References
Jeong, H., Tombor, B., Albert, R., Oltvai, Z.N., Barabsi, A.L.: The large- scale organization of metabolic networks. Nature 407(6804), 651–654 (2000)
Strogatz, S.H.: Exploring complex networks. Nature 410(6825), 268–276 (2001)
Albet, R., Barabsi, A.L.: Statistical mechanics of complex networks. Rev. Mod. Phys. 74(1), 47–91 (2002)
Cao, B., Li, D., Li, B.: Complex network topology mining and community detection. Dyn. Continuous Discrete Impulsive Systems Ser. B: Appl. Algorithms 13(3), 361–370 (2006)
Zhu, L., Lai, Y.C., Hoppensteadt, F.C., He, J.: Characterization of neural interaction during learning and adaptation from spike-train data. Math. Biosci. Eng. 2(1), 1–23 (2005)
Goto, S., Nishioka, T., Kanehisa, M.: Chemical database for enzyme reactions. Bioinformatics 14(7), 591–599 (1998)
Horne, A.B., Hodgman, T.C., Spence, H.D., Dalby, A.R.: Constructing an enzyme-centric view of metabolism. Bioinformatics 20(13), 2050–2055 (2004)
Jin, C.W., Marsden, I., Chen, X.Q., Liao, X.B.: Dynamic DNA contacts observed in the NMR structure of winged helix protein-DNA complex. J. Mol. Biol. 289, 683–690 (1999)
Stauffer, D., Penna, T.J.P.: Crossover in the Cont-Bouchaud percolation model for market fluctuations. Physica A 256, 284–290 (1998)
Wang, N., Wang, J.: Fluctuation model for stock market index based on continuous percolation. J. Beijingjiaotong University 28(6), 36–38 (2004)
Fang, Y., Kincaid, T.G.: Stability analysis of dynamical neural networks. IEEE Trans. Neural Networks 7(4), 996–1006 (1996)
Watts, D.J., Strogatz, S.H.: Collective dynamics of ’small-world’ networks. Nature 391(4), 440–442 (1998)
Barabasi, A.L., Albet, R.: Emergence of scaling in random networks. Science 286(15), 509–512 (1999)
Pecora, L.M., Carroll, T.L.: Master stability function for synchronized coupled systems. Phys. Rev. Lett. 80(10), 2109–2112 (1998)
Wang, X.F., Chen, G.: Synchronization in small-world dynamical networks. Int. J. Bifur. Chaos 12(1), 187–192 (2002)
Tang, W.K.S., Mao, Y., Kocarev, L.: Identification and monitoring of neural network. In: IEEE International Symposium on Circuits and Systems, May 27-30, pp. 2646–2649 (2007)
Zheng, S., Bi, Q.H., Cai, G.L.: Adaptive projective synchronization in complex networks with time-varying coupling delay. Physics Letters A 373(17), 1553–1559 (2009)
Lu, J.Q., Cao, J.D.: Synchronization-based approach for parameters identification in delayed chaotic neural networks. Phys. A 382, 672–682 (2007)
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Lu, D., Qi, Q. (2011). Adaptive Projective Synchronization of Complex Networks with Weighted Topology. In: Zhang, J. (eds) Applied Informatics and Communication. ICAIC 2011. Communications in Computer and Information Science, vol 226. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23235-0_18
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DOI: https://doi.org/10.1007/978-3-642-23235-0_18
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