Littérature scientifique sur le sujet « Dynamical models on networks »
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Articles de revues sur le sujet "Dynamical models on networks"
Innocenti, Giacomo, et Paolo Paoletti. « Embedding dynamical networks into distributed models ». Communications in Nonlinear Science and Numerical Simulation 24, no 1-3 (juillet 2015) : 21–39. http://dx.doi.org/10.1016/j.cnsns.2014.12.009.
Texte intégralPiqueira, José R. C., et Felipe Barbosa Cesar. « Dynamical Models for Computer Viruses Propagation ». Mathematical Problems in Engineering 2008 (2008) : 1–11. http://dx.doi.org/10.1155/2008/940526.
Texte intégralMalyshev, V. A. « Networks and dynamical systems ». Advances in Applied Probability 25, no 01 (mars 1993) : 140–75. http://dx.doi.org/10.1017/s0001867800025210.
Texte intégralMalyshev, V. A. « Networks and dynamical systems ». Advances in Applied Probability 25, no 1 (mars 1993) : 140–75. http://dx.doi.org/10.2307/1427500.
Texte intégralHouse, Thomas, et Matt J. Keeling. « Insights from unifying modern approximations to infections on networks ». Journal of The Royal Society Interface 8, no 54 (10 juin 2010) : 67–73. http://dx.doi.org/10.1098/rsif.2010.0179.
Texte intégralYeung, Enoch, Jongmin Kim, Ye Yuan, Jorge Gonçalves et Richard M. Murray. « Data-driven network models for genetic circuits from time-series data with incomplete measurements ». Journal of The Royal Society Interface 18, no 182 (septembre 2021) : 20210413. http://dx.doi.org/10.1098/rsif.2021.0413.
Texte intégralCESSAC, B. « A VIEW OF NEURAL NETWORKS AS DYNAMICAL SYSTEMS ». International Journal of Bifurcation and Chaos 20, no 06 (juin 2010) : 1585–629. http://dx.doi.org/10.1142/s0218127410026721.
Texte intégralCAO, QI, GUILHERME RAMOS, PAUL BOGDAN et SÉRGIO PEQUITO. « THE ACTUATION SPECTRUM OF SPATIOTEMPORAL NETWORKS WITH POWER-LAW TIME DEPENDENCIES ». Advances in Complex Systems 22, no 07n08 (novembre 2019) : 1950023. http://dx.doi.org/10.1142/s0219525919500231.
Texte intégralHasani, Ramin, Mathias Lechner, Alexander Amini, Daniela Rus et Radu Grosu. « Liquid Time-constant Networks ». Proceedings of the AAAI Conference on Artificial Intelligence 35, no 9 (18 mai 2021) : 7657–66. http://dx.doi.org/10.1609/aaai.v35i9.16936.
Texte intégralWANG, XIAO FAN. « COMPLEX NETWORKS : TOPOLOGY, DYNAMICS AND SYNCHRONIZATION ». International Journal of Bifurcation and Chaos 12, no 05 (mai 2002) : 885–916. http://dx.doi.org/10.1142/s0218127402004802.
Texte intégralThèses sur le sujet "Dynamical models on networks"
Tupikina, Liubov. « Temporal and spatial aspects of correlation networks and dynamical network models ». Doctoral thesis, Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät, 2017. http://dx.doi.org/10.18452/17746.
Texte intégralIn the thesis I studied the complex architectures of networks, the network evolution in time, the interpretation of the networks measures and a particular class of processes taking place on complex networks. Firstly, I derived the measures to characterize temporal networks evolution in order to detect spatial variability patterns in evolving systems. Secondly, I introduced a novel flow-network method to construct networks from flows, that also allows to modify the set-up from purely relying on the velocity field. The flow-network method is developed for correlations of a scalar quantity (temperature, for example), which satisfies advection-diffusion dynamics in the presence of forcing and dissipation. This allows to characterize transport in the fluids, to identify various mixing regimes in the flow and to apply this method to advection-diffusion dynamics, data from climate and other systems, where particles transport plays a crucial role. Thirdly, I developed a novel Heterogeneous Opinion-Status model (HOpS) and analytical technique to study dynamical processes on networks. All in all, methods, derived in the thesis, allow to quantify evolution of various classes of complex systems, to get insight into physical meaning of correlation networks and analytically to analyze processes, taking place on networks.
DI, GANGI Domenico. « Models of dynamical networks with applications to finance ». Doctoral thesis, Scuola Normale Superiore, 2022. http://hdl.handle.net/11384/112204.
Texte intégralPreciado, Víctor Manuel. « Spectral analysis for stochastic models of large-scale complex dynamical networks ». Thesis, Massachusetts Institute of Technology, 2008. http://hdl.handle.net/1721.1/45873.
Texte intégralIncludes bibliographical references (p. 179-196).
Research on large-scale complex networks has important applications in diverse systems of current interest, including the Internet, the World-Wide Web, social, biological, and chemical networks. The growing availability of massive databases, computing facilities, and reliable data analysis tools has provided a powerful framework to explore structural properties of such real-world networks. However, one cannot efficiently retrieve and store the exact or full topology for many large-scale networks. As an alternative, several stochastic network models have been proposed that attempt to capture essential characteristics of such complex topologies. Network researchers then use these stochastic models to generate topologies similar to the complex network of interest and use these topologies to test, for example, the behavior of dynamical processes in the network. In general, the topological properties of a network are not directly evident in the behavior of dynamical processes running on it. On the other hand, the eigenvalue spectra of certain matricial representations of the network topology do relate quite directly to the behavior of many dynamical processes of interest, such as random walks, Markov processes, virus/rumor spreading, or synchronization of oscillators in a network. This thesis studies spectral properties of popular stochastic network models proposed in recent years. In particular, we develop several methods to determine or estimate the spectral moments of these models. We also present a variety of techniques to extract relevant spectral information from a finite sequence of spectral moments. A range of numerical examples throughout the thesis confirms the efficacy of our approach. Our ultimate objective is to use such results to understand and predict the behavior of dynamical processes taking place in large-scale networks.
by Víctor Manuel Preciado.
Ph.D.
He, Ping. « Robust synchronization of dynamical networks with delay and uncertainty :synthesis & ; application ». Thesis, University of Macau, 2017. http://umaclib3.umac.mo/record=b3691044.
Texte intégralNath, Madhurima. « Application of Network Reliability to Analyze Diffusive Processes on Graph Dynamical Systems ». Diss., Virginia Tech, 2019. http://hdl.handle.net/10919/86841.
Texte intégralPh. D.
The research presented here explores the effects of the structural properties of an interacting system on the outcomes of a diffusive process using Moore-Shannon network reliability. The network reliability is a finite degree polynomial which provides the probability of observing a certain configuration for a diffusive process on networks. Examples of such processes analyzed here are outbreak of an epidemic in a population, spread of an invasive species through international trade of commodities and spread of a perturbation in a physical system with discrete magnetic spins. Network reliability is a novel tool which can be used to compare the efficiency of network models with the observed data, to find important components of the system as well as to estimate the functions of thermodynamic state variables.
McLoone, Seamus Cornelius. « Nonlinear identification using local model networks ». Thesis, Queen's University Belfast, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.326349.
Texte intégralGong, Xue. « Dynamical Systems in Cell Division Cycle, Winnerless Competition Models, and Tensor Approximations ». Ohio University / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1458303716.
Texte intégralHellmann, Tim. « Stable networks in static and dynamic models of network formation ». Hamburg Kovač, 2009. http://d-nb.info/1001547497/04.
Texte intégralLi, Caiwei. « Dynamic scheduling of multiclass queueing networks ». Diss., Georgia Institute of Technology, 2000. http://hdl.handle.net/1853/24339.
Texte intégralSIRI, ENRICO. « Dynamic traffic assignment models for disrupted networks ». Doctoral thesis, Università degli studi di Genova, 2022. http://hdl.handle.net/11567/1091373.
Texte intégralLivres sur le sujet "Dynamical models on networks"
Traag, Vincent. Algorithms and Dynamical Models for Communities and Reputation in Social Networks. Cham : Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-06391-1.
Texte intégralStavros, Siokos, dir. Financial networks : Statics and dynamics. Berlin : Springer-Verlag, 1997.
Trouver le texte intégralMenache, Ishai. Network games : Theory, models, and dynamics. San Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA) : Morgan & Claypool, 2011.
Trouver le texte intégralA, Arbib Michael, Amari Shun'ichi et U.S.-Japan Seminar on Competition and Cooperation in Neural Nets (1987 : University of Southern California), dir. Dynamic interactions in neural networks : Models and data. New York : Springer-Verlag, 1989.
Trouver le texte intégralG, Chen. Fundamentals of complex networks : Models, structures, and dynamics. Singapore : John Wiley & Sons Inc., 2015.
Trouver le texte intégralArbib, Michael A., et Shun-ichi Amari, dir. Dynamic Interactions in Neural Networks : Models and Data. New York, NY : Springer New York, 1989. http://dx.doi.org/10.1007/978-1-4612-4536-0.
Texte intégralAldo, Romano, et SpringerLink (Online service), dir. Dynamic Learning Networks : Models and Cases in Action. Boston, MA : Springer-Verlag US, 2009.
Trouver le texte intégralM, Harris-Warrick Ronald, dir. Dynamic biological networks : The stomatogastric nervous system. Cambridge, Mass : MIT Press, 1992.
Trouver le texte intégralAura, Reggiani, et Nijkamp Peter, dir. Spatial dynamics, networks and modelling. Cheltenham, UK : Edward Elgar, 2006.
Trouver le texte intégralH, Gartner Nathan, Improta Gennaro 1942- et International Seminar on Urban Traffic Networks (2nd : 1992 : Capri, Italy), dir. Urban traffic networks : Dynamic flow modeling and control. Berlin : Springer-Verlag, 1995.
Trouver le texte intégralChapitres de livres sur le sujet "Dynamical models on networks"
Elhadj, Zeraoulia. « Robust Chaos in Neural Networks Models ». Dans Dynamical Systems, 96–116. Boca Raton, FL : CRC Press, 2019. | “A science publishers book.” : CRC Press, 2019. http://dx.doi.org/10.1201/9780429028939-4.
Texte intégralSporns, Olaf, Giulio Tononi et Gerald M. Edelman. « Reentry and Dynamical Interactions of Cortical Networks ». Dans Models of Neural Networks, 315–41. New York, NY : Springer New York, 1994. http://dx.doi.org/10.1007/978-1-4612-4320-5_9.
Texte intégralMeng, Ziyang, Tao Yang et Karl H. Johansson. « Networked Dynamical System Models ». Dans Systems & ; Control : Foundations & ; Applications, 21–27. Cham : Springer International Publishing, 2012. http://dx.doi.org/10.1007/978-3-030-84682-4_3.
Texte intégralBoccara, Nino. « Automata Network Models of Interacting Populations ». Dans Cellular Automata, Dynamical Systems and Neural Networks, 23–77. Dordrecht : Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-017-1005-3_2.
Texte intégralNagurney, Anna, et Stavros Siokos. « Dynamic Imperfect Market Models ». Dans Financial Networks, 278–94. Berlin, Heidelberg : Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/978-3-642-59066-5_10.
Texte intégralNagurney, Anna, et Stavros Siokos. « Dynamic Single Country Models ». Dans Financial Networks, 218–49. Berlin, Heidelberg : Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/978-3-642-59066-5_8.
Texte intégralAbou-Jaoudé, Wassim, Jérôme Feret et Denis Thieffry. « Derivation of Qualitative Dynamical Models from Biochemical Networks ». Dans Computational Methods in Systems Biology, 195–207. Cham : Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-23401-4_17.
Texte intégralAmari, Shun-ichi. « Dynamical Stability of Formation of Cortical Maps ». Dans Dynamic Interactions in Neural Networks : Models and Data, 15–34. New York, NY : Springer New York, 1989. http://dx.doi.org/10.1007/978-1-4612-4536-0_2.
Texte intégralKinzel, Wolfgang, et Manfred Opper. « Dynamics of Learning ». Dans Models of Neural Networks, 149–71. Berlin, Heidelberg : Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/978-3-642-97171-6_4.
Texte intégralAddison, J. D., et B. G. Heydecker. « Traffic Models for Dynamic Assignment ». Dans Urban Traffic Networks, 213–31. Berlin, Heidelberg : Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/978-3-642-79641-8_8.
Texte intégralActes de conférences sur le sujet "Dynamical models on networks"
Pasa, Luca, Alessandro Sperduti et Peter Tino. « Linear dynamical based models for sequential domains ». Dans 2017 International Joint Conference on Neural Networks (IJCNN). IEEE, 2017. http://dx.doi.org/10.1109/ijcnn.2017.7966122.
Texte intégralBove, Pasquale, Alessio Micheli, Paolo Milazzo et Marco Podda. « Prediction of Dynamical Properties of Biochemical Pathways with Graph Neural Networks ». Dans 11th International Conference on Bioinformatics Models, Methods and Algorithms. SCITEPRESS - Science and Technology Publications, 2020. http://dx.doi.org/10.5220/0008964700320043.
Texte intégralOuyang, Zhengyu, et Mingzhou Song. « Statistical Analysis of Discrete Dynamical System Models for Biological Networks ». Dans 2009 International Joint Conference on Bioinformatics, Systems Biology and Intelligent Computing. IEEE, 2009. http://dx.doi.org/10.1109/ijcbs.2009.10.
Texte intégralRevay, Max, Ruigang Wang et Ian R. Manchester. « Recurrent Equilibrium Networks : Unconstrained Learning of Stable and Robust Dynamical Models ». Dans 2021 60th IEEE Conference on Decision and Control (CDC). IEEE, 2021. http://dx.doi.org/10.1109/cdc45484.2021.9683054.
Texte intégralWang, Bo, Sergey Nersesov et Hashem Ashrafiuon. « Formation Control for Underactuated Surface Vessel Networks ». Dans ASME 2020 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/dscc2020-3178.
Texte intégralChaouiya, Claudine, Aurelien Naldi, Elisabeth Remy et Denis Thieffry. « Reduction of logical models of regulatory networks yields insight into dynamical properties ». Dans Control (MSC). IEEE, 2010. http://dx.doi.org/10.1109/cca.2010.5611238.
Texte intégralMoriya, Satoshi, Hideaki Yamamoto, Ayumi Hirano-Iwata, Shigeru Kubota et Shigeo Sato. « Quantitative Analysis of Dynamical Complexity in Cultured Neuronal Network Models for Reservoir Computing Applications ». Dans 2019 International Joint Conference on Neural Networks (IJCNN). IEEE, 2019. http://dx.doi.org/10.1109/ijcnn.2019.8852207.
Texte intégralYang, Chun-Lin, et C. Steve Suh. « On the Dynamics of Complex Network ». Dans ASME 2017 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/imece2017-71994.
Texte intégralDan Wang, Xiaolong Qian et Xiaozheng Jin. « Dynamical evolution of weighted scale-free network models ». Dans 2012 24th Chinese Control and Decision Conference (CCDC). IEEE, 2012. http://dx.doi.org/10.1109/ccdc.2012.6244073.
Texte intégralCrippa, Paolo, Francesco Gianfelici et Claudio Turchetti. « Information theoretical algorithm based on statistical models for blind identification of nonstationary dynamical systems ». Dans 2009 International Joint Conference on Neural Networks (IJCNN 2009 - Atlanta). IEEE, 2009. http://dx.doi.org/10.1109/ijcnn.2009.5178880.
Texte intégralRapports d'organisations sur le sujet "Dynamical models on networks"
Hirsch, Morris W., Bill Baird, Walter Freeman et Bernice Gangale. Dynamical Systems, Neural Networks and Cortical Models ASSERT 93. Fort Belvoir, VA : Defense Technical Information Center, novembre 1994. http://dx.doi.org/10.21236/ada295495.
Texte intégralAbarbanel, Henry, et Philip Gill. Parameter Estimation and Model Validation of Nonlinear Dynamical Networks. Office of Scientific and Technical Information (OSTI), mars 2015. http://dx.doi.org/10.2172/1177970.
Texte intégralYu, Haichao, Haoxiang Li, Honghui Shi, Thomas S. Huang et Gang Hua. Any-Precision Deep Neural Networks. Web of Open Science, décembre 2020. http://dx.doi.org/10.37686/ejai.v1i1.82.
Texte intégralSaito, Kazumi. Dynamic Trust Models between Users over Social Networks. Fort Belvoir, VA : Defense Technical Information Center, mars 2016. http://dx.doi.org/10.21236/ada636879.
Texte intégralLi, Jing. Various New Statistical Models for Modeling and Change Detection in Multidimensional Dynamic Networks. Fort Belvoir, VA : Defense Technical Information Center, janvier 2014. http://dx.doi.org/10.21236/ada606729.
Texte intégralThai, My. Combating Weapons of Mass Destruction : Models, Complexity, and Algorithms in Complex Dynamic and Evolving Networks. Fort Belvoir, VA : Defense Technical Information Center, novembre 2015. http://dx.doi.org/10.21236/ada625120.
Texte intégralUtsugi, Akio, et Motoyuki Akamatsu. Analysis of Car-Following Behavior Using Dynamic Probabilistic Models~Identification of Driving Mode Transition Using Dynamic Bayesian Networks. Warrendale, PA : SAE International, mai 2005. http://dx.doi.org/10.4271/2005-08-0241.
Texte intégralEngel, Bernard, Yael Edan, James Simon, Hanoch Pasternak et Shimon Edelman. Neural Networks for Quality Sorting of Agricultural Produce. United States Department of Agriculture, juillet 1996. http://dx.doi.org/10.32747/1996.7613033.bard.
Texte intégralField, Richard V.,, Hamilton E. Link, Jacek Skryzalin et Jeremy D. Wendt. A dynamic model for social networks. Office of Scientific and Technical Information (OSTI), septembre 2018. http://dx.doi.org/10.2172/1472229.
Texte intégralLiu, Ernest, et Aleh Tsyvinski. Dynamical Structure and Spectral Properties of Input-Output Networks. Cambridge, MA : National Bureau of Economic Research, décembre 2020. http://dx.doi.org/10.3386/w28178.
Texte intégral