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Chung, Spectral Graph Theory, American Mathematical Soc., 1997.","DOI":"10.1090\/cbms\/092"},{"key":"2","doi-asserted-by":"publisher","unstructured":"[2] D.J. Aldous, \u201cSome inequalities for reversible markov chains,\u201d J. London Math. Soc., vol.2, no.3, pp.564-576, 1982. 10.1112\/jlms\/s2-25.3.564","DOI":"10.1112\/jlms\/s2-25.3.564"},{"key":"3","doi-asserted-by":"publisher","unstructured":"[3] S. Boyd, P. Diaconis, P. Parrilo, and L. Xiao, \u201cFastest mixing markov chain on graphs with symmetries,\u201d SIAM J. Optimiz., vol.20, no.2, pp.792-819, 2009. 10.1137\/070689413","DOI":"10.1137\/070689413"},{"key":"4","doi-asserted-by":"publisher","unstructured":"[4] M. Barahona and L.M. Pecora, \u201cSynchronization in small-world systems,\u201d Phys. Rev. Lett., vol.89, no.5, p.054101, 2002. 10.1103\/physrevlett.89.054101","DOI":"10.1103\/PhysRevLett.89.054101"},{"key":"5","doi-asserted-by":"publisher","unstructured":"[5] S. Boccaletti, V. Latora, Y. Moreno, M. Chavez, and D.U. Hwang, \u201cComplex networks: Structure and dynamics,\u201d Physics Reports, vol.424, no.4, pp.175-308, 2006. 10.1016\/j.physrep.2005.10.009","DOI":"10.1016\/j.physrep.2005.10.009"},{"key":"6","doi-asserted-by":"crossref","unstructured":"[6] A. Arenas, A. Diaz-Guilera, and C.J. P\u00e9rez-Vicente, \u201cSynchronization reveals topological scales in complex networks,\u201d Phys. Rev. Lett., vol.96, no.11, p.114102, 2006. 10.1103\/physrevlett.96.114102","DOI":"10.1103\/PhysRevLett.96.114102"},{"key":"7","doi-asserted-by":"crossref","unstructured":"[7] P.N. McGraw and M. Menzinger, \u201cAnalysis of nonlinear synchronization dynamics of oscillator networks by Laplacian spectral methods,\u201d Phys. Rev. E, vol.75, no.2, p.027104, 2007. 10.1103\/physreve.75.027104","DOI":"10.1103\/PhysRevE.75.027104"},{"key":"8","doi-asserted-by":"crossref","unstructured":"[8] V.M. Preciado and A. Jadbabaie, \u201cSpectral analysis of virus spreading in random geometric networks,\u201d Decision and Control, 2009 held jointly with the 2009 28th Chinese Control Conference. CDC\/CCC 2009. Proc. 48th IEEE Conference on, pp.4802-4807, IEEE, 2009. 10.1109\/cdc.2009.5400615","DOI":"10.1109\/CDC.2009.5400615"},{"key":"9","unstructured":"[9] P. Van Mieghem and J. Omic, \u201cIn-homogeneous virus spread in networks,\u201d arXiv preprint arXiv:1306.2588, 2013."},{"key":"10","unstructured":"[10] M. Aida, C. Takano, and M. Murata, \u201cOscillation model for network dynamics caused by asymmetric node interaction based on the symmetric scaled Laplacian matrix,\u201d Proc. International Conference on Foundations of Computer Science (FCS), pp.38-44, The Steering Committee of The World Congress in Computer Science, Computer Engineering and Applied Computing (WorldComp), 2016."},{"key":"11","doi-asserted-by":"publisher","unstructured":"[11] M. Aida, C. Takano, and M. Murata, \u201cOscillation model for describing network dynamics caused by asymmetric node interaction,\u201d IEICE Trans. Commun., vol.E101-B, no.1, pp.123-136, Jan. 2018. 10.1587\/transcom.2017ebn0001","DOI":"10.1587\/transcom.2017EBN0001"},{"key":"12","doi-asserted-by":"crossref","unstructured":"[12] S. Furutani, C. Takano, and M. Aida, \u201cProposal of the network resonance method for estimating eigenvalues of the scaled Laplacian matrix,\u201d Proc. International Conference on Intelligent Networking and Collaborative Systems (INCoS), pp.451-456, IEEE, 2016. 10.1109\/incos.2016.70","DOI":"10.1109\/INCoS.2016.70"},{"key":"13","doi-asserted-by":"crossref","unstructured":"[13] S. Furutani, C. Takano, and M. Aida, \u201cMethod for estimating the eigenvectors of a scaled Laplacian matrix using the resonance of oscillation dynamics on networks,\u201d Proc. International Conference on Advances in social networks analysis and mining (ASONAM), pp.615-618, IEEE\/ACM, 2017. 10.1145\/3110025.3110043","DOI":"10.1145\/3110025.3110043"},{"key":"14","doi-asserted-by":"crossref","unstructured":"[14] M. Newman, Networks: An Introduction, Oxford University Press, 2010.","DOI":"10.1093\/acprof:oso\/9780199206650.003.0001"},{"key":"15","doi-asserted-by":"publisher","unstructured":"[15] Y. Li and Z.L. Zhang, \u201cDigraph Laplacian and the degree of asymmetry,\u201d Internet Mathematics, vol.8, no.4, pp.381-401, 2012. 10.1080\/15427951.2012.708890","DOI":"10.1080\/15427951.2012.708890"},{"key":"16","doi-asserted-by":"crossref","unstructured":"[16] C. Takano and M. Aida, \u201cProposal of new index for describing node centralities based on oscillation dynamics on network,\u201d Proc. Global Communications Conference (GLOBECOM), pp.1-7, IEEE, 2016. 10.1109\/glocom.2016.7842177","DOI":"10.1109\/GLOCOM.2016.7842177"},{"key":"17","doi-asserted-by":"crossref","unstructured":"[17] C. Takano and M. Aida, \u201cFundamental framework for describing various node centralities using an oscillation model on social media networks,\u201d Communications (ICC), 2017 IEEE International Conference on, pp.1-6, IEEE, 2017. 10.1109\/icc.2017.7996913","DOI":"10.1109\/ICC.2017.7996913"},{"key":"18","doi-asserted-by":"publisher","unstructured":"[18] A.L. Barab\u00e1si and R. Albert, \u201cEmergence of scaling in random networks,\u201d Science, vol.286, no.5439, pp.509-512, 1999. 10.1126\/science.286.5439.509","DOI":"10.1126\/science.286.5439.509"},{"key":"19","unstructured":"[19] N. Hirakura, C. Takano, and M. Aida, \u201cEfficient orthogonalizing the eigenvectors of the Laplacian matrix to estimate social network structure,\u201d NOLTA, pp.180-183, IEICE, 2018."},{"key":"20","doi-asserted-by":"crossref","unstructured":"[20] B.D. MacArthur and R.J. S\u00e1nchez-Garc\u00eda, \u201cSpectral characteristics of network redundancy,\u201d Phys. Rev. E, vol.80, no.2, p.026117, 2009. 10.1103\/physreve.80.026117","DOI":"10.1103\/PhysRevE.80.026117"},{"key":"21","doi-asserted-by":"crossref","unstructured":"[21] S. Sugimoto and M. Aida, \u201cEstimating the structure of social networks from incomplete set of observed information by using compressed sensing,\u201d Proc. IEEE Latin-American Conference on Communications (LATINCOM), IEEE, 2017. 10.1109\/latincom.2017.8240162","DOI":"10.1109\/LATINCOM.2017.8240162"},{"key":"22","doi-asserted-by":"publisher","unstructured":"[22] S. Jalan and J.N. Bandyopadhyay, \u201cRandom matrix analysis of network laplacians,\u201d Physica A: Statistical Mechanics and its Applications, vol.387, no.2-3, pp.667-674, 2008. 10.1016\/j.physa.2007.09.026","DOI":"10.1016\/j.physa.2007.09.026"},{"key":"23","doi-asserted-by":"crossref","unstructured":"[23] D. Yu, M. Righero, and L. Kocarev, \u201cEstimating topology of networks,\u201d Phys. Rev. Lett., vol.97, no.18, p.188701, 2006. 10.1103\/physrevlett.97.188701","DOI":"10.1103\/PhysRevLett.97.188701"},{"key":"24","doi-asserted-by":"publisher","unstructured":"[24] D. Yu, \u201cEstimating the topology of complex dynamical networks by steady state control: Generality and limitation,\u201d Automatica, vol.46, no.12, pp.2035-2040, 2010. 10.1016\/j.automatica.2010.08.010","DOI":"10.1016\/j.automatica.2010.08.010"},{"key":"25","doi-asserted-by":"publisher","unstructured":"[25] D. Yu and U. Parlitz, \u201cDriving a network to steady states reveals its cooperative architecture,\u201d Europhys. Lett., vol.81, no.4, p.48007, 2008. 10.1209\/0295-5075\/81\/48007","DOI":"10.1209\/0295-5075\/81\/48007"},{"key":"26","doi-asserted-by":"publisher","unstructured":"[26] M. Timme, \u201cRevealing network connectivity from response dynamics,\u201d Phys. Rev. Lett., vol.98, no.22, p.224101, 2007. 10.1103\/physrevlett.98.224101","DOI":"10.1103\/PhysRevLett.98.224101"},{"key":"27","doi-asserted-by":"publisher","unstructured":"[27] M. Timme and J. Casadiego, \u201cRevealing networks from dynamics: An introduction,\u201d J. Phys. A: Math. Theor., vol.47, no.34, p.343001, 2014. 10.1088\/1751-8113\/47\/34\/343001","DOI":"10.1088\/1751-8113\/47\/34\/343001"},{"key":"28","unstructured":"[28] Y. Kuramoto, Chemical Oscillations, Waves, and Turbulence, Springer Science &amp; Business Media, 2012."},{"key":"29","doi-asserted-by":"publisher","unstructured":"[29] M. Franceschelli, A. Gasparri, A. Giua, and C. Seatzu, \u201cDecentralized estimation of Laplacian eigenvalues in multi-agent systems,\u201d Automatica, vol.49, no.4, pp.1031-1036, 2013. 10.1016\/j.automatica.2013.01.029","DOI":"10.1016\/j.automatica.2013.01.029"},{"key":"30","doi-asserted-by":"publisher","unstructured":"[30] A. Mauroy and J. Hendrickx, \u201cSpectral identification of networks using sparse measurements,\u201d SIAM J. Appl. Dyn. Syst., vol.16, no.1, pp.479-513, 2017. 10.1137\/16m105722x","DOI":"10.1137\/16M105722X"},{"key":"31","unstructured":"[31] A. Mauroy and J. Hendrickx, \u201cSpectral identification of networks with inputs,\u201d arXiv preprint arXiv:1709.04153, 2017."},{"key":"32","unstructured":"[32] R. Brincker, L. Zhang, and P. Andersen, \u201cModal identification from ambient responses using frequency domain decomposition,\u201d Proc. 18th International Modal Analysis Conference (IMAC), 2000."},{"key":"33","doi-asserted-by":"publisher","unstructured":"[33] R. Brincker, L. Zhang, and P. Andersen, \u201cModal identification of output-only systems using frequency domain decomposition,\u201d Smart Mater. Struct., vol.10, no.3, pp.441-445, 2001. 10.1088\/0964-1726\/10\/3\/303","DOI":"10.1088\/0964-1726\/10\/3\/303"},{"key":"34","doi-asserted-by":"crossref","unstructured":"[34] S. Mertens, \u201cThe easiest hard problem: Number partitioning,\u201d Computational Complexity and Statistical Physics, vol.125, no.2, pp.125-139, 2006.","DOI":"10.1093\/oso\/9780195177374.003.0012"},{"key":"35","unstructured":"[35] I.P. Gent and T. Walsh, \u201cPhase transitions and annealed theories: Number partitioning as a case study,\u201d ECAI, pp.170-174, PITMAN, 1996."},{"key":"36","doi-asserted-by":"publisher","unstructured":"[36] J.P. Pedroso and M. Kubo, \u201cHeuristics and exact methods for number partitioning,\u201d Eur. J. Oper. Res., vol.202, no.1, pp.73-81, 2010. 10.1016\/j.ejor.2009.04.027","DOI":"10.1016\/j.ejor.2009.04.027"},{"key":"37","doi-asserted-by":"publisher","unstructured":"[37] R.E. Korf, \u201cA complete anytime algorithm for number partitioning,\u201d Artif. 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