Academic literature on the topic 'Dynamical models on networks'
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Journal articles on the topic "Dynamical models on networks"
Innocenti, Giacomo, and Paolo Paoletti. "Embedding dynamical networks into distributed models." Communications in Nonlinear Science and Numerical Simulation 24, no. 1-3 (July 2015): 21–39. http://dx.doi.org/10.1016/j.cnsns.2014.12.009.
Full textPiqueira, José R. C., and 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.
Full textMalyshev, V. A. "Networks and dynamical systems." Advances in Applied Probability 25, no. 01 (March 1993): 140–75. http://dx.doi.org/10.1017/s0001867800025210.
Full textMalyshev, V. A. "Networks and dynamical systems." Advances in Applied Probability 25, no. 1 (March 1993): 140–75. http://dx.doi.org/10.2307/1427500.
Full textHouse, Thomas, and Matt J. Keeling. "Insights from unifying modern approximations to infections on networks." Journal of The Royal Society Interface 8, no. 54 (June 10, 2010): 67–73. http://dx.doi.org/10.1098/rsif.2010.0179.
Full textYeung, Enoch, Jongmin Kim, Ye Yuan, Jorge Gonçalves, and 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 (September 2021): 20210413. http://dx.doi.org/10.1098/rsif.2021.0413.
Full textCESSAC, B. "A VIEW OF NEURAL NETWORKS AS DYNAMICAL SYSTEMS." International Journal of Bifurcation and Chaos 20, no. 06 (June 2010): 1585–629. http://dx.doi.org/10.1142/s0218127410026721.
Full textCAO, QI, GUILHERME RAMOS, PAUL BOGDAN, and SÉRGIO PEQUITO. "THE ACTUATION SPECTRUM OF SPATIOTEMPORAL NETWORKS WITH POWER-LAW TIME DEPENDENCIES." Advances in Complex Systems 22, no. 07n08 (November 2019): 1950023. http://dx.doi.org/10.1142/s0219525919500231.
Full textHasani, Ramin, Mathias Lechner, Alexander Amini, Daniela Rus, and Radu Grosu. "Liquid Time-constant Networks." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 9 (May 18, 2021): 7657–66. http://dx.doi.org/10.1609/aaai.v35i9.16936.
Full textWANG, XIAO FAN. "COMPLEX NETWORKS: TOPOLOGY, DYNAMICS AND SYNCHRONIZATION." International Journal of Bifurcation and Chaos 12, no. 05 (May 2002): 885–916. http://dx.doi.org/10.1142/s0218127402004802.
Full textDissertations / Theses on the topic "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.
Full textIn 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.
Full textPreciado, 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.
Full textIncludes 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.
Full textNath, Madhurima. "Application of Network Reliability to Analyze Diffusive Processes on Graph Dynamical Systems." Diss., Virginia Tech, 2019. http://hdl.handle.net/10919/86841.
Full textPh. 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.
Full textGong, 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.
Full textHellmann, Tim. "Stable networks in static and dynamic models of network formation." Hamburg Kovač, 2009. http://d-nb.info/1001547497/04.
Full textLi, Caiwei. "Dynamic scheduling of multiclass queueing networks." Diss., Georgia Institute of Technology, 2000. http://hdl.handle.net/1853/24339.
Full textSIRI, ENRICO. "Dynamic traffic assignment models for disrupted networks." Doctoral thesis, Università degli studi di Genova, 2022. http://hdl.handle.net/11567/1091373.
Full textBooks on the topic "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.
Full textStavros, Siokos, ed. Financial networks: Statics and dynamics. Berlin: Springer-Verlag, 1997.
Find full textMenache, Ishai. Network games: Theory, models, and dynamics. San Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA): Morgan & Claypool, 2011.
Find full textA, Arbib Michael, Amari Shun'ichi, and U.S.-Japan Seminar on Competition and Cooperation in Neural Nets (1987 : University of Southern California), eds. Dynamic interactions in neural networks: Models and data. New York: Springer-Verlag, 1989.
Find full textG, Chen. Fundamentals of complex networks: Models, structures, and dynamics. Singapore: John Wiley & Sons Inc., 2015.
Find full textArbib, Michael A., and Shun-ichi Amari, eds. 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.
Full textAldo, Romano, and SpringerLink (Online service), eds. Dynamic Learning Networks: Models and Cases in Action. Boston, MA: Springer-Verlag US, 2009.
Find full textM, Harris-Warrick Ronald, ed. Dynamic biological networks: The stomatogastric nervous system. Cambridge, Mass: MIT Press, 1992.
Find full textAura, Reggiani, and Nijkamp Peter, eds. Spatial dynamics, networks and modelling. Cheltenham, UK: Edward Elgar, 2006.
Find full textH, Gartner Nathan, Improta Gennaro 1942-, and International Seminar on Urban Traffic Networks (2nd : 1992 : Capri, Italy), eds. Urban traffic networks: Dynamic flow modeling and control. Berlin: Springer-Verlag, 1995.
Find full textBook chapters on the topic "Dynamical models on networks"
Elhadj, Zeraoulia. "Robust Chaos in Neural Networks Models." In 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.
Full textSporns, Olaf, Giulio Tononi, and Gerald M. Edelman. "Reentry and Dynamical Interactions of Cortical Networks." In 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.
Full textMeng, Ziyang, Tao Yang, and Karl H. Johansson. "Networked Dynamical System Models." In Systems & Control: Foundations & Applications, 21–27. Cham: Springer International Publishing, 2012. http://dx.doi.org/10.1007/978-3-030-84682-4_3.
Full textBoccara, Nino. "Automata Network Models of Interacting Populations." In 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.
Full textNagurney, Anna, and Stavros Siokos. "Dynamic Imperfect Market Models." In Financial Networks, 278–94. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/978-3-642-59066-5_10.
Full textNagurney, Anna, and Stavros Siokos. "Dynamic Single Country Models." In Financial Networks, 218–49. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/978-3-642-59066-5_8.
Full textAbou-Jaoudé, Wassim, Jérôme Feret, and Denis Thieffry. "Derivation of Qualitative Dynamical Models from Biochemical Networks." In Computational Methods in Systems Biology, 195–207. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-23401-4_17.
Full textAmari, Shun-ichi. "Dynamical Stability of Formation of Cortical Maps." In 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.
Full textKinzel, Wolfgang, and Manfred Opper. "Dynamics of Learning." In Models of Neural Networks, 149–71. Berlin, Heidelberg: Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/978-3-642-97171-6_4.
Full textAddison, J. D., and B. G. Heydecker. "Traffic Models for Dynamic Assignment." In Urban Traffic Networks, 213–31. Berlin, Heidelberg: Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/978-3-642-79641-8_8.
Full textConference papers on the topic "Dynamical models on networks"
Pasa, Luca, Alessandro Sperduti, and Peter Tino. "Linear dynamical based models for sequential domains." In 2017 International Joint Conference on Neural Networks (IJCNN). IEEE, 2017. http://dx.doi.org/10.1109/ijcnn.2017.7966122.
Full textBove, Pasquale, Alessio Micheli, Paolo Milazzo, and Marco Podda. "Prediction of Dynamical Properties of Biochemical Pathways with Graph Neural Networks." In 11th International Conference on Bioinformatics Models, Methods and Algorithms. SCITEPRESS - Science and Technology Publications, 2020. http://dx.doi.org/10.5220/0008964700320043.
Full textOuyang, Zhengyu, and Mingzhou Song. "Statistical Analysis of Discrete Dynamical System Models for Biological Networks." In 2009 International Joint Conference on Bioinformatics, Systems Biology and Intelligent Computing. IEEE, 2009. http://dx.doi.org/10.1109/ijcbs.2009.10.
Full textRevay, Max, Ruigang Wang, and Ian R. Manchester. "Recurrent Equilibrium Networks: Unconstrained Learning of Stable and Robust Dynamical Models." In 2021 60th IEEE Conference on Decision and Control (CDC). IEEE, 2021. http://dx.doi.org/10.1109/cdc45484.2021.9683054.
Full textWang, Bo, Sergey Nersesov, and Hashem Ashrafiuon. "Formation Control for Underactuated Surface Vessel Networks." In ASME 2020 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/dscc2020-3178.
Full textChaouiya, Claudine, Aurelien Naldi, Elisabeth Remy, and Denis Thieffry. "Reduction of logical models of regulatory networks yields insight into dynamical properties." In Control (MSC). IEEE, 2010. http://dx.doi.org/10.1109/cca.2010.5611238.
Full textMoriya, Satoshi, Hideaki Yamamoto, Ayumi Hirano-Iwata, Shigeru Kubota, and Shigeo Sato. "Quantitative Analysis of Dynamical Complexity in Cultured Neuronal Network Models for Reservoir Computing Applications." In 2019 International Joint Conference on Neural Networks (IJCNN). IEEE, 2019. http://dx.doi.org/10.1109/ijcnn.2019.8852207.
Full textYang, Chun-Lin, and C. Steve Suh. "On the Dynamics of Complex Network." In ASME 2017 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/imece2017-71994.
Full textDan Wang, Xiaolong Qian, and Xiaozheng Jin. "Dynamical evolution of weighted scale-free network models." In 2012 24th Chinese Control and Decision Conference (CCDC). IEEE, 2012. http://dx.doi.org/10.1109/ccdc.2012.6244073.
Full textCrippa, Paolo, Francesco Gianfelici, and Claudio Turchetti. "Information theoretical algorithm based on statistical models for blind identification of nonstationary dynamical systems." In 2009 International Joint Conference on Neural Networks (IJCNN 2009 - Atlanta). IEEE, 2009. http://dx.doi.org/10.1109/ijcnn.2009.5178880.
Full textReports on the topic "Dynamical models on networks"
Hirsch, Morris W., Bill Baird, Walter Freeman, and Bernice Gangale. Dynamical Systems, Neural Networks and Cortical Models ASSERT 93. Fort Belvoir, VA: Defense Technical Information Center, November 1994. http://dx.doi.org/10.21236/ada295495.
Full textAbarbanel, Henry, and Philip Gill. Parameter Estimation and Model Validation of Nonlinear Dynamical Networks. Office of Scientific and Technical Information (OSTI), March 2015. http://dx.doi.org/10.2172/1177970.
Full textYu, Haichao, Haoxiang Li, Honghui Shi, Thomas S. Huang, and Gang Hua. Any-Precision Deep Neural Networks. Web of Open Science, December 2020. http://dx.doi.org/10.37686/ejai.v1i1.82.
Full textSaito, Kazumi. Dynamic Trust Models between Users over Social Networks. Fort Belvoir, VA: Defense Technical Information Center, March 2016. http://dx.doi.org/10.21236/ada636879.
Full textLi, Jing. Various New Statistical Models for Modeling and Change Detection in Multidimensional Dynamic Networks. Fort Belvoir, VA: Defense Technical Information Center, January 2014. http://dx.doi.org/10.21236/ada606729.
Full textThai, My. Combating Weapons of Mass Destruction: Models, Complexity, and Algorithms in Complex Dynamic and Evolving Networks. Fort Belvoir, VA: Defense Technical Information Center, November 2015. http://dx.doi.org/10.21236/ada625120.
Full textUtsugi, Akio, and Motoyuki Akamatsu. Analysis of Car-Following Behavior Using Dynamic Probabilistic Models~Identification of Driving Mode Transition Using Dynamic Bayesian Networks. Warrendale, PA: SAE International, May 2005. http://dx.doi.org/10.4271/2005-08-0241.
Full textEngel, Bernard, Yael Edan, James Simon, Hanoch Pasternak, and Shimon Edelman. Neural Networks for Quality Sorting of Agricultural Produce. United States Department of Agriculture, July 1996. http://dx.doi.org/10.32747/1996.7613033.bard.
Full textField, Richard V.,, Hamilton E. Link, Jacek Skryzalin, and Jeremy D. Wendt. A dynamic model for social networks. Office of Scientific and Technical Information (OSTI), September 2018. http://dx.doi.org/10.2172/1472229.
Full textLiu, Ernest, and Aleh Tsyvinski. Dynamical Structure and Spectral Properties of Input-Output Networks. Cambridge, MA: National Bureau of Economic Research, December 2020. http://dx.doi.org/10.3386/w28178.
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