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Synchronization on Complex Networks of Networks
IEEE Transactions on Neural Networks and Learning Systems, 2014In this paper, pinning synchronization on complex networks of networks is investigated, where there are many subnetworks with the interactions among them. The subnetworks and their connections can be regarded as the nodes and interactions of the networks, respectively, which form the networks of networks.
Renquan Lu, Wenwu Yu, Jinhu Lu
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Physical Review E, 2020
Large populations of globally coupled or uncoupled oscillators have been recently shown to exhibit an intriguing echo behavior [Ott, Platig, Antonsen, and Girvan, Chaos: An Interdiscip. J. Nonlinear Sci. 18, 037115 (2008)CHAOEH1054-150010.1063/1.2973816; Chen, Tinsley, Ott, and Showalter, Phys. Rev. X 6, 041054 (2016)2160-330810.1103/PhysRevX.6.041054],
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Large populations of globally coupled or uncoupled oscillators have been recently shown to exhibit an intriguing echo behavior [Ott, Platig, Antonsen, and Girvan, Chaos: An Interdiscip. J. Nonlinear Sci. 18, 037115 (2008)CHAOEH1054-150010.1063/1.2973816; Chen, Tinsley, Ott, and Showalter, Phys. Rev. X 6, 041054 (2016)2160-330810.1103/PhysRevX.6.041054],
Richa, Phogat +2 more
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2020 IEEE 19th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC), 2020
The Internet, social networks, power grids, gene regulatory networks, neuronal systems, food webs, social systems, and networks emanating from augmented and virtual reality platforms are all examples of complex networks. Collection and analysis of data from these networks is essential for their understanding.
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The Internet, social networks, power grids, gene regulatory networks, neuronal systems, food webs, social systems, and networks emanating from augmented and virtual reality platforms are all examples of complex networks. Collection and analysis of data from these networks is essential for their understanding.
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Network complexity and generalization
Proceedings of International Conference on Neural Networks (ICNN'97), 2002This paper explains the relationship between complexity of the neural network with sigmoidal hidden neurons and its generalization capability in function approximation. Network complexity is decided in terms of the number of degrees of freedom and their dynamic range.
Sangbong Park, Cheol Hoon Park
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The Complexity of Terrorist Networks
2008 12th International Conference Information Visualisation, 2008Complexity science affords a number of novel tools for examining terrorism, particularly network analysis and NK-Boolean fitness landscapes. The following paper explores various aspects of terrorist networks which can be illuminated through applications of non-linear dynamical systems modeling to terrorist network structures. Of particular interest are
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Controllability of complex networks
Nature, 2011The ultimate proof of our understanding of natural or technological systems is reflected in our ability to control them. Although control theory offers mathematical tools for steering engineered and natural systems towards a desired state, a framework to control complex self-organized systems is lacking.
Yang-Yu, Liu +2 more
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2018
[Excerpt] In recent years, the emergence of a large amount of data dispersed in several types of databases enabled the extraction of information on a never seen scale. Complex networks allow the connection of a vast amount of scattered and unstructured data in order to understand relations, construct models for their interpretation, analyze structures,
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[Excerpt] In recent years, the emergence of a large amount of data dispersed in several types of databases enabled the extraction of information on a never seen scale. Complex networks allow the connection of a vast amount of scattered and unstructured data in order to understand relations, construct models for their interpretation, analyze structures,
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On the Complexity of Network Synchronization
SIAM Journal on Computing, 2004We show that if a minimal-time solution to a fundamental distributed computation primitive, synchronizing a network path of finite-state processors, exists on the three-dimensional, undirected grid, then we can conclude the purely complexity-theoretic result P=NP. Every previous result on network synchronization for various network topologies either
Darin Goldstein, Kojiro Kobayashi
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