Academic literature on the topic 'Time-varying network'
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Journal articles on the topic "Time-varying network"
Crane, Harry. "Time-varying network models." Bernoulli 21, no. 3 (August 2015): 1670–96. http://dx.doi.org/10.3150/14-bej617.
Full textYu, Hui, Yi Zhang, and Gao Yang Liu. "Multi-Agent Consensus with a Time-Varying Reference State and Time-Varying Delays." Applied Mechanics and Materials 48-49 (February 2011): 724–29. http://dx.doi.org/10.4028/www.scientific.net/amm.48-49.724.
Full textLucas, Maxime, Duccio Fanelli, Timoteo Carletti, and Julien Petit. "Desynchronization induced by time-varying network." EPL (Europhysics Letters) 121, no. 5 (May 10, 2018): 50008. http://dx.doi.org/10.1209/0295-5075/121/50008.
Full textCarchiolo, Vincenza, Christian Cavallo, Marco Grassia, Michele Malgeri, and Giuseppe Mangioni. "Link Prediction in Time Varying Social Networks." Information 13, no. 3 (March 1, 2022): 123. http://dx.doi.org/10.3390/info13030123.
Full textWang, Li Fu, Jian Ding, and Zhi Kong. "Local Synchronization for Time Varying Topological Networks." Advanced Materials Research 850-851 (December 2013): 545–48. http://dx.doi.org/10.4028/www.scientific.net/amr.850-851.545.
Full textHammachukiattikul, Porpattama. "Finite-time Stability, Dissipativity and Passivity Analysis of Discrete-time Neural Networks Time-varying Delays." Emerging Science Journal 3, no. 6 (December 1, 2019): 361–68. http://dx.doi.org/10.28991/esj-2019-01198.
Full textSharma, Vicky, Koushik Kar, Richard La, and Leandros Tassiulas. "Dynamic network provisioning for time-varying traffic." Journal of Communications and Networks 9, no. 4 (December 2007): 408–18. http://dx.doi.org/10.1109/jcn.2007.6182876.
Full textZhaoyan Wu and Xiaoli Gong. "IMPULSIVE SYNCHRONIZATION OF TIME-VARYING DYNAMICAL NETWORK." Journal of Applied Analysis & Computation 6, no. 1 (2016): 94–102. http://dx.doi.org/10.11948/2016008.
Full textMyung, Hyun, and Jong-Hwan Kim. "Time-Varying Two-Phase Optimization Neural Network." Journal of Intelligent and Fuzzy Systems 5, no. 2 (1997): 85–101. http://dx.doi.org/10.3233/ifs-1997-5201.
Full textKhamfroush, Hana, Daniel E. Lucani, Joao Barros, and Peyman Pahlevani. "Network-Coded Cooperation Over Time-Varying Channels." IEEE Transactions on Communications 62, no. 12 (December 2014): 4413–25. http://dx.doi.org/10.1109/tcomm.2014.2367016.
Full textDissertations / Theses on the topic "Time-varying network"
Afrasiabi, Rad Amir. "Social Network Analysis and Time Varying Graphs." Thesis, Université d'Ottawa / University of Ottawa, 2016. http://hdl.handle.net/10393/34441.
Full textKhan, Asif H. "Analysis of time varying load for minimum loss distribution reconfiguration." Diss., This resource online, 1992. http://scholar.lib.vt.edu/theses/available/etd-06062008-171313/.
Full textReber, David Patrick. "Exponential Stability of Intrinsically Stable Dynamical Networks and Switched Networks with Time-Varying Time Delays." BYU ScholarsArchive, 2019. https://scholarsarchive.byu.edu/etd/7136.
Full textOlanders, David. "Optimal Time-Varying Cash Allocation." Thesis, KTH, Matematisk statistik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-273626.
Full textEn betalning är den mest fundamentala aspekten av handel som involverar kapital. De senaste åren har utvecklingen av nya betalmedel ökat drastiskt då världen fortsatt att utvecklas genom digitaliseringen. Utvecklingen har lett till en ökad efterfrågan på digitala betalningslösningar som kan hantera handel över hela världen. Då handel idag kan ske när som helst oberoende av var betalaren och betalningsmottagaren befinner sig, måste systemet som genomför betalningen alltid vara tillgängligt för att kunna förmedla handel mellan olika parter. Detta kräver att betalningssystemet alltid måste ha medel tillgängligt i efterfrågade länder och valutor för att handeln ska kunna genomföras. Den här uppsatsen fokuserar på hur kapital kostnadseffektivt kan omallokeras i ett betalsystem för att säkerställa att handel alltid är tillgängligt. Traditionellt har omallokeringen av kapital gjorts på ett regelbaserat sätt, vilket inte tagit hänsyn till kostnadsdimensionen och därigenom enbart fokuserat på själva omallokeringen. Den här uppsatsen använder metoder för att optimalt omallokera kapital baserat på kostnaderna för omallokeringen. Därigenom skapas en möjlighet att flytta kapital på ett avsevärt mer kostnadseffektivt sätt. När omallokeringsbesluten formuleras matematiskt som ett optimeringsproblem är kostnadsfunktionen formulerad som ett linjärt program med både Booleska och reella begränsningar av variablerna. Detta gör att traditionella lösningsmetoder för linjära program inte är användningsbara för att finna den optimala lösningen, varför vidareutveckling av tradtionella metoder tillsammans med mer avancerade metoder använts. Modellen utvärderades baserat på ett stort antal simuleringar som jämförde dess prestanda med det regelbaserade systemet. Den utvecklade modellen presterar en signfikant kostnadsreduktion i jämförelse med det regelbaserade systemet och överträffar därigenom det traditionellt använda systemet. Framtida arbete bör fokusera på att expandera modellen genom att utöka de potentiella överföringsmöjligheterna, att ta ökad hänsyn till osäkerhet genom en bayesiansk hantering, samt slutligen att integrera samtliga kostnadsaspekter i nätverket.
Maråk, Knut Petter. "The Time Varying Elastance Model used as a Boundary Condition in Arterial Network Simulations." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for konstruksjonsteknikk, 2013. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-23203.
Full textNakajima, Natsu. "Genetic Network Completion Using Dynamic Programming and Least-Squares Fitting." 京都大学 (Kyoto University), 2015. http://hdl.handle.net/2433/195987.
Full textUnsal, Ahmet Dundar. "Estimation Of Time-dependent Link Costs Using Gps Track Data." Master's thesis, METU, 2006. http://etd.lib.metu.edu.tr/upload/3/12608010/index.pdf.
Full textthey rarely exist on back roads, secondary roads and streets due to their deployment costs. Today, telematics systems offer fleet operators to track their fleet remotely from a central system. Those systems provide data about the behaviors of vehicles with time information. Therefore, a tracking system can be used as an alternative to detector-based systems on estimating travel speeds on networks. This study aims to provide methods to estimate network characteristics using the data collected directly from fleets consisting of global positioning system (GPS) receiver equipped vehicles. GIS technology is used to process the collected GPS data spatially to match digital road maps. After matching, time-dependent characteristics of roads on which tracked vehicles traveled are estimated. This estimation provides data to perform a time-dependent network analysis. The methods proposed in this study are tested on traffic network of Middle East Technical University campus. The results showed that the proposed methods are capable of measuring time-dependent link-travel times on the network. Peak hours through the network are clearly detected.
Liang, Qingkai. "Survivability of time-varying networks." Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/98694.
Full textCataloged from PDF version of thesis.
Includes bibliographical references (pages 81-83).
Time-varying graphs are a useful model for networks with dynamic connectivity such as mmWave networks and vehicular networks, yet, despite their great modeling power, many important features of time-varying graphs are still poorly understood. In this thesis, we study the survivability properties of time-varying networks against unpredictable interruptions. We first show that the traditional definition of survivability is not effective in time-varying networks and propose a new survivability framework. To evaluate survivability of time-varying networks under the new framework, we propose two metrics that are analogous to MaxFlow and MinCut in static networks. We show that some fundamental survivability-related results such as Menger's Theorem only conditionally hold in timevarying networks. Then we analyze the complexity of computing the proposed metrics and develop several approximation algorithms. Finally, we conduct trace-driven simulations to demonstrate the application of our survivability framework in the robust design of a real-world bus communication network.
by Qingkai Liang.
S.M.
Slind, Jillian Rae. "Community detection in sparse time-varying networks." Thesis, University of British Columbia, 2014. http://hdl.handle.net/2429/50043.
Full textScience, Faculty of
Computer Science, Department of
Graduate
Demircin, Mehmet Umut. "Robust video streaming over time-varying wireless networks." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/24790.
Full textCommittee Chair: Yucel Altunbasak; Committee Member: Chuanyi Ji; Committee Member: Ghassan AlRegib; Committee Member: Ozlem Ergun; Committee Member: Russell M. Mersereau.
Books on the topic "Time-varying network"
Mukherjee, Animesh. Dynamics On and Of Complex Networks, Volume 2: Applications to Time-Varying Dynamical Systems. New York, NY: Springer New York, 2013.
Find full textDror, Shahar. Identification and control of non-linear time-varying dynamical systems using artificial neural networks. Monterey, Calif: Naval Postgraduate School, 1992.
Find full textWong, C. K., and Dan Sha. Time-Varying Network Optimization. Springer London, Limited, 2007.
Find full textTime-Varying Network Optimization. Boston, MA: Springer US, 2007. http://dx.doi.org/10.1007/0-387-71215-1.
Full textTime-Varying Network Optimization (International Series in Operations Research & Management Science). Springer, 2007.
Find full textGanguly, Niloy, Animesh Mukherjee, Monojit Choudhury, Fernando Peruani, and Bivas Mitra. Dynamics On and Of Complex Networks, Volume 2: Applications to Time-Varying Dynamical Systems. Birkhäuser, 2015.
Find full textDong, Hongli, Zidong Wang, and Nan Hou. Networked Non-Linear Stochastic Time-varying Systems. Taylor & Francis Group, 2021.
Find full textNetworked Non-Linear Stochastic Time-Varying Systems: Analysis and Synthesis. Taylor & Francis Group, 2021.
Find full textDong, Hongli, Zidong Wang, and Nan Hou. Networked Non-Linear Stochastic Time-Varying Systems: Analysis and Synthesis. Taylor & Francis Group, 2021.
Find full textDong, Hongli, Zidong Wang, and Nan Hou. Networked Non-Linear Stochastic Time-Varying Systems: Analysis and Synthesis. Taylor & Francis Group, 2021.
Find full textBook chapters on the topic "Time-varying network"
Dong, Hongli, Zidong Wang, and Nan Hou. "Distributed Estimation over Sensor Network." In Networked Nonlinear Stochastic Time-Varying Systems, 119–58. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781003189497-6.
Full textZhu, Jun-Wei, Xin Wang, and Guang-Hong Yang. "IE for Time-Varying Delay Systems." In Fault Estimation for Network Systems via Intermediate Estimator, 43–53. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-6321-6_4.
Full textKarsai, Márton, and Nicola Perra. "Control Strategies of Contagion Processes in Time-Varying Networks." In Temporal Network Epidemiology, 179–97. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-5287-3_8.
Full textShen, Yi, Meiqin Liu, and Xiaodong Xu. "Stochastic Time-Varying Competitive Neural Network Systems." In Advances in Neural Networks - ISNN 2006, 683–88. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11759966_100.
Full textSha, D., X. Cai, and C. K. Wong. "The Maximum Flow in a Time-Varying Network." In Lecture Notes in Economics and Mathematical Systems, 437–56. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/978-3-642-57014-8_29.
Full textWu, Yuanqing, Renquan Lu, Hongye Su, Peng Shi, and Zheng-Guang Wu. "Sampled-Data Control with Time-Varying Coupling Delay." In Synchronization Control for Large-Scale Network Systems, 67–91. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-45150-3_4.
Full textMarcastel, Alexandre, E. Veronica Belmega, Panayotis Mertikopoulos, and Inbar Fijalkow. "Interference Mitigation via Pricing in Time-Varying Cognitive Radio Systems." In Network Games, Control, and Optimization, 177–86. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-51034-7_17.
Full textLi, Zhan, and Yunong Zhang. "Time-Varying Quadratic Programming by Zhang Neural Network Equipped with a Time-Varying Design Parameter γ(t)." In Advances in Neural Networks – ISNN 2011, 101–8. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-21105-8_13.
Full textSquartini, Stefano, Yibin Ye, and Francesco Piazza. "Learning Capabilities of ELM-Trained Time-Varying Neural Networks." In Recent Advances of Neural Network Models and Applications, 41–52. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-04129-2_5.
Full textJiang, Dingguo. "Finite Time Stability of Cohen-Grossberg Neural Network with Time-Varying Delays." In Advances in Neural Networks – ISNN 2009, 522–31. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-01507-6_60.
Full textConference papers on the topic "Time-varying network"
Nakajima, Natsu, and Tatsuya Akutsu. "Network Completion for Time Varying Genetic Networks." In 2013 7th International Conference on Complex, Intelligent, and Software Intensive Systems (CISIS). IEEE, 2013. http://dx.doi.org/10.1109/cisis.2013.100.
Full textBaohua, Fan, Zhang Heying, and Dou Wenhua. "A Time Varying Network Calculus." In 2009 Fifth International Joint Conference on INC, IMS and IDC. IEEE, 2009. http://dx.doi.org/10.1109/ncm.2009.230.
Full textTomasi, Federico, Veronica Tozzo, Saverio Salzo, and Alessandro Verri. "Latent Variable Time-varying Network Inference." In KDD '18: The 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3219819.3220121.
Full textStoorvogel, Anton A., Ali Saberi, and Meirong Zhang. "Synchronization in an homogeneous, time-varying network with nonuniform time-varying communication delays." In 2016 IEEE 55th Conference on Decision and Control (CDC). IEEE, 2016. http://dx.doi.org/10.1109/cdc.2016.7798383.
Full textNadini, Matthieu, Alessandro Rizzo, and Maurizio Porfiri. "Contagion Processes Over Temporal Networks With Time-Varying Backbones." In ASME 2019 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/dscc2019-9054.
Full textIkeda, Takuya, and Kenji Kashima. "Optimal time-varying topology for network systems." In 2022 13th Asian Control Conference (ASCC). IEEE, 2022. http://dx.doi.org/10.23919/ascc56756.2022.9828074.
Full textKapetanaki, Alexandra, Konstantinos Kopsidas, C. Tumelo-Chakonta, and Muhhamad Buhari. "Network planning evaluation implementing time varying thermal ratings." In 2014 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS). IEEE, 2014. http://dx.doi.org/10.1109/pmaps.2014.6960663.
Full textUchimura, Y. "Wireless network based control with time varying delay." In IECON 2008 - 34th Annual Conference of IEEE Industrial Electronics Society. IEEE, 2008. http://dx.doi.org/10.1109/iecon.2008.4758431.
Full textLi, Yize, and Jie Tang. "Expertise Search in a Time-Varying Social Network." In 2008 9th International Conference on Web-Age Information Management (WAIM). IEEE, 2008. http://dx.doi.org/10.1109/waim.2008.100.
Full textHallac, David, Youngsuk Park, Stephen Boyd, and Jure Leskovec. "Network Inference via the Time-Varying Graphical Lasso." In KDD '17: The 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3097983.3098037.
Full textReports on the topic "Time-varying network"
Shrader, Brooke, Armen Babikyan, Nathaniel M. Jones, Thomas H. Shake, and Andrew P. Worthen. Rate Control for Network-Coded Multipath Relaying with Time-Varying Connectivity. Fort Belvoir, VA: Defense Technical Information Center, December 2010. http://dx.doi.org/10.21236/ada540462.
Full textDew-Becker, Ian, Alireza Tahbaz-Salehi, and Andrea Vedolin. Skewness and Time-Varying Second Moments in a Nonlinear Production Network: Theory and Evidence. Cambridge, MA: National Bureau of Economic Research, November 2021. http://dx.doi.org/10.3386/w29499.
Full textMiller-Hooks, E. D., and H. S. Mahmassani. Least expected time paths in stochastic, time-varying transportation networks. Office of Scientific and Technical Information (OSTI), June 1999. http://dx.doi.org/10.2172/350896.
Full textWoods, A. L., E. Miller-Hooks, and H. S. Mahmassani. Optimal routing of hazardous substances in time-varying, stochastic transportation networks. Office of Scientific and Technical Information (OSTI), July 1998. http://dx.doi.org/10.2172/663396.
Full textGearhart, Jared Lee, and Nolan Scot Kurtz. Time-Varying, Multi-Scale Adaptive System Reliability Analysis of Lifeline Infrastructure Networks. Office of Scientific and Technical Information (OSTI), September 2014. http://dx.doi.org/10.2172/1259845.
Full textBowler, L. A., and H. S. Mahmassani. Routing of radioactive shipments in networks with time-varying costs and curfews. Office of Scientific and Technical Information (OSTI), September 1998. http://dx.doi.org/10.2172/291124.
Full textKushner, Harold J. Scheduling and Control of Mobile Communications Networks with Randomly Time Varying Channels by Stability Methods. Fort Belvoir, VA: Defense Technical Information Center, January 2006. http://dx.doi.org/10.21236/ada458950.
Full textMiles, Gaines E., Yael Edan, F. Tom Turpin, Avshalom Grinstein, Thomas N. Jordan, Amots Hetzroni, Stephen C. Weller, Marvin M. Schreiber, and Okan K. Ersoy. Expert Sensor for Site Specification Application of Agricultural Chemicals. United States Department of Agriculture, August 1995. http://dx.doi.org/10.32747/1995.7570567.bard.
Full textBielinskyi, Andrii O., Serhii V. Hushko, Andriy V. Matviychuk, Oleksandr A. Serdyuk, Сергій Олексійович Семеріков, Володимир Миколайович Соловйов, Андрій Іванович Білінський, Андрій Вікторович Матвійчук, and О. А. Сердюк. Irreversibility of financial time series: a case of crisis. Криворізький державний педагогічний університет, December 2021. http://dx.doi.org/10.31812/123456789/6975.
Full textEvent-Triggered Adaptive Robust Control for Lateral Stability of Steer-by-Wire Vehicles with Abrupt Nonlinear Faults. SAE International, July 2022. http://dx.doi.org/10.4271/2022-01-5056.
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