Academic literature on the topic 'Time-varying network'

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Journal articles on the topic "Time-varying network"

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Crane, Harry. "Time-varying network models." Bernoulli 21, no. 3 (August 2015): 1670–96. http://dx.doi.org/10.3150/14-bej617.

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Yu, 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.

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This paper is devoted to the study of consensus problem of multi-agent systems with a time-varying reference state in directed networks with both switching topology and time-delay. Stability analysis is performed based on a proposed Lyapunov–Krasovskii function. Sufficient conditions based on linear matrix inequalities (LMIs) are given to guarantee that multi-agent consensus on a time-varying reference state can be achieved under arbitrary switching of the network topology even if the network communication is affected by time-delay. These consensus algorithms are also extended to consensus formation among the agents. Finally, simulation example is given to validate our theoretical results.
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Lucas, 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.

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Carchiolo, 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.

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Predicting new links in complex networks can have a large societal impact. In fact, many complex systems can be modeled through networks, and the meaning of the links depend on the system itself. For instance, in social networks, where the nodes are users, links represent relationships (such as acquaintance, friendship, etc.), whereas in information spreading networks, nodes are users and content and links represent interactions, diffusion, etc. However, while many approaches involve machine learning-based algorithms, just the most recent ones account for the topology of the network, e.g., geometric deep learning techniques to learn on graphs, and most of them do not account for the temporal dynamics in the network but train on snapshots of the system at a given time. In this paper, we aim to explore Temporal Graph Networks (TGN), a Graph Representation Learning-based approach that natively supports dynamic graphs and assigns to each event (link) a timestamp. In particular, we investigate how the TGN behaves when trained under different temporal granularity or with various event aggregation techniques when learning the inductive and transductive link prediction problem on real social networks such as Twitter, Wikipedia, Yelp, and Reddit. We find that initial setup affects the temporal granularity of the data, but the impact depends on the specific social network. For instance, we note that the train batch size has a strong impact on Twitter, Wikipedia, and Yelp, while it does not matter on Reddit.
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Wang, 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.

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In this paper, local synchronization problem of complex networks is theoretically and numerically studied. Base on the Lyapunov stability theory, a sufficient criterion for local synchronization of complex network which have the time-varying connection topologies is derived via designed decentralized linear controllers. And a numerical example of typical the Rössler network system with time-varying linear coupling has been used to demonstrate and verify the proposed. And, the simulation results show the effectiveness of proposed synchronization approaches.
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Hammachukiattikul, 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.

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The neural network time-varying delay was described as the dynamic properties of a neural cell, including neural functional and neural delay differential equations. The differential expression explains the derivative term of current and past state. The objective of this paper obtained the neural network time-varying delay. A delay-dependent condition is provided to ensure the considered discrete-time neural networks with time-varying delays to be finite-time stability, dissipativity, and passivity. This paper using a new Lyapunov-Krasovskii functional as well as the free-weighting matrix approach and a linear matrix inequality analysis (LMI) technique constructing to a novel sufficient criterion on finite-time stability, dissipativity, and passivity of the discrete-time neural networks with time-varying delays for improving. We propose sufficient conditions for discrete-time neural networks with time-varying delays. An effective LMI approach derives by base the appropriate type of Lyapunov functional. Finally, we present the effectiveness of novel criteria of finite-time stability, dissipativity, and passivity condition of discrete-time neural networks with time-varying delays in the form of linear matrix inequality (LMI).
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Sharma, 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.

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Zhaoyan 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.

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Myung, 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.

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Khamfroush, 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.

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Dissertations / Theses on the topic "Time-varying network"

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Afrasiabi, Rad Amir. "Social Network Analysis and Time Varying Graphs." Thesis, Université d'Ottawa / University of Ottawa, 2016. http://hdl.handle.net/10393/34441.

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The thesis focuses on the social web and on the analysis of social networks with particular emphasis on their temporal aspects. Social networks are represented here by Time Varying Graphs (TVG), a general model for dynamic graphs borrowed from distributed computing. In the first part of the thesis we focus on the temporal aspects of social networks. We develop various temporal centrality measures for TVGs including betweenness, closeness, and eigenvector centralities, which are well known in the context of static graphs. Unfortunately the computational complexities of these temporal centrality metrics are not comparable with their static counterparts. For example, the computation of betweenness becomes intractable in the dynamic setting. For this reason, approximation techniques will also be considered. We apply these temporal measures to two very different datasets, one in the context of knowledge mobilization in a small community of university researchers, the other in the context of Facebook commenting activities among a large number of web users. In both settings, we perform a temporal analysis so to understand the importance of the temporal factors in the dynamics of those networks and to detect nodes that act as “accelerators”. In the second part of the thesis, we focus on a more standard static graph representation. We conduct a propagation study on YouTube datasets to understand and compare the propagation dynamics of two different types of users: subscribers and friends. Finally, we conclude the thesis with the proposal of a general framework to present, in a comprehensive model, the influence of the social web on e-commerce decision making.
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Khan, 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/.

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Reber, 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.

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Dynamic processes on real-world networks are time-delayed due to finite processing speeds and the need to transmit data over nonzero distances. These time-delays often destabilize the network's dynamics, but are difficult to analyze because they increase the dimension of the network.We present results outlining an alternative means of analyzing these networks, by focusing analysis on the Lipschitz matrix of the relatively low-dimensional undelayed network. The key criteria, intrinsic stability, is computationally efficient to verify by use of the power method. We demonstrate applications from control theory and neural networks.
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Olanders, David. "Optimal Time-Varying Cash Allocation." Thesis, KTH, Matematisk statistik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-273626.

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A payment is the most fundamental aspect of a trade that involves funds. In recent years, the development of new payment services has accelerated significantly as the world has moved further into the digital era. This transition has led to an increased demand of digital payment solutions that can handle trades across the world. As trades today can be agreed at any time wherever the payer and payee are located, the party that mediates payments must at any time to be available in order to mediate an agreed exchange. This requires the payment service provider to always have funds available in the required countries and currencies in order for trades to always be available. This thesis concerns how a payment service provider can reallocate capital in a cost efficient way in order for trades to always be available. Traditionally, the reallocation of capital is done in a rule-based manner, which discard the cost dimension and thereby only focus on the reallocation itself. This thesis concerns methods to optimally reallocate capital focusing on the cost of transferring capital within the network. Where the concerned methods has the potential of transferring capital in a far more cost efficient way. When mathematically formulating the reallocation decisions as an optimization problem, the cost function is formulated as a linear program with both Boolean and real constraints. This impose non-feasibility of locating the optimal solution using traditional methods for linear programs, why developed traditional and more advanced methods were used. The model was evaluated based on a large number of simulations in comparison with the performance of a rule-based reallocation system. The developed model provides a significant cost reduction compared to the rule-based approach and thereby outperforms the traditional reallocation system. Future work should focus on expanding the model by broadening the available transfer options, by increasing the considered uncertainty via a bayesian treatment and finally by considering all cost aspects of the network.
En 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.
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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.

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Vascular1Dflow is a program for simulating blood flow in vascular networks. It uses hyperbolic one-dimensional partial differential equations with ordinary differential equations as boundary conditions. The focus of this work has been the development boundary conditions, primarily a time varying elastance model of the left ventricle has been implemented as a boundary condition. The aortic and mitral valves were modeled using a mathematical valve model. The varying elastance model is tested in lumped model and arterial network simulations. An improved solution algorithm for computing pressure and flow at bifurcations is implemented and tested. Also a improved discretization scheme for Windkessel models is presented.
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Nakajima, Natsu. "Genetic Network Completion Using Dynamic Programming and Least-Squares Fitting." 京都大学 (Kyoto University), 2015. http://hdl.handle.net/2433/195987.

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Unsal, 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.

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Intelligent Transport Systems (ITS) are becoming a part of our daily lives in various forms of application. Their success depends highly on the accuracy of the digital data they use. In networks where characteristics change by time, time-based network analysis algorithms provide results that are more accurate. However, these analyses require time-based travel speed data to provide accurate results. Conventionally, traffic data are usually obtained using the data provided from loop-detectors. These detectors usually exist on main arteries, freeways and highways
they 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.
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Liang, Qingkai. "Survivability of time-varying networks." Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/98694.

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Thesis: S.M., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2015.
Cataloged 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.
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Slind, Jillian Rae. "Community detection in sparse time-varying networks." Thesis, University of British Columbia, 2014. http://hdl.handle.net/2429/50043.

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Community detection is an important aspect of network analysis that has far-reaching consequences, in particular for biological research. In the study of systems biology, it is important to detect communities in biological networks to identify areas that have a heavy correlation between one another or are significant for biological functions. If one were to model networks that evolved over time, a differential network would be a vital part or product of that analysis. One such network could have an edge between two vertices if there is a significant change in the correlation of expression levels between the two genes that the vertices are designed to model. For this particular network, there are no community detection algorithms that suffice. An analysis of the current community detection algorithms shows that most heuristic-based methods are too simple or have too high a cost for detecting communities on such sparse networks. A prototypical algorithm is presented that is preferential to high weight edges when determining community membership. This algorithm, Weighted Sparse Community Finder or WSCF, is an incremental algorithm that develops community structure from highly-weighted community seeds, which are 3-vertex substructures in the network with a high local modularity. A preliminary analysis of this detection algorithm shows that it is functional on data sets consisting of up to 600 genes, with more on a more powerful machine. The communities detected are different than the ones provided by the benchmark algorithms because of the high precedence placed on higher-weight edges. This prototypical algorithm has the potential for refinement and expansion to provide the ability to find significant results for applications in the field of Systems Biology.
Science, Faculty of
Computer Science, Department of
Graduate
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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.

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Thesis (Ph.D.)--Electrical and Computer Engineering, Georgia Institute of Technology, 2009.
Committee Chair: Yucel Altunbasak; Committee Member: Chuanyi Ji; Committee Member: Ghassan AlRegib; Committee Member: Ozlem Ergun; Committee Member: Russell M. Mersereau.
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Books on the topic "Time-varying network"

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Mukherjee, Animesh. Dynamics On and Of Complex Networks, Volume 2: Applications to Time-Varying Dynamical Systems. New York, NY: Springer New York, 2013.

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Dror, Shahar. Identification and control of non-linear time-varying dynamical systems using artificial neural networks. Monterey, Calif: Naval Postgraduate School, 1992.

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Wong, C. K., and Dan Sha. Time-Varying Network Optimization. Springer London, Limited, 2007.

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Time-Varying Network Optimization. Boston, MA: Springer US, 2007. http://dx.doi.org/10.1007/0-387-71215-1.

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Time-Varying Network Optimization (International Series in Operations Research & Management Science). Springer, 2007.

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Ganguly, 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.

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Dong, Hongli, Zidong Wang, and Nan Hou. Networked Non-Linear Stochastic Time-varying Systems. Taylor & Francis Group, 2021.

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Networked Non-Linear Stochastic Time-Varying Systems: Analysis and Synthesis. Taylor & Francis Group, 2021.

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Dong, Hongli, Zidong Wang, and Nan Hou. Networked Non-Linear Stochastic Time-Varying Systems: Analysis and Synthesis. Taylor & Francis Group, 2021.

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Dong, Hongli, Zidong Wang, and Nan Hou. Networked Non-Linear Stochastic Time-Varying Systems: Analysis and Synthesis. Taylor & Francis Group, 2021.

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Book chapters on the topic "Time-varying network"

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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.

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Zhu, 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.

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Karsai, 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.

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Shen, 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.

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Sha, 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.

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Wu, 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.

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Marcastel, 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.

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Li, 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.

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Squartini, 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.

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Jiang, 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.

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Conference papers on the topic "Time-varying network"

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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.

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Baohua, 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.

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Tomasi, 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.

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Stoorvogel, 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.

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Nadini, 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.

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Abstract Predicting the diffusion of real-world contagion processes requires a simplified description of human-to-human interactions. Temporal networks offer a powerful means to develop such a mathematically-transparent description. Through temporal networks, one may analytically study the co-evolution of the contagion process and the network topology, as well as incorporate realistic feedback-loop mechanisms related to individual behavioral changes to the contagion. Despite considerable progress, the state-of-the-art does not allow for studying general time-varying networks, where links between individuals dynamically switch to reflect the complexity of social behavior. Here, we tackle this problem by considering a temporal network, in which reducible, associated with node-specific properties, and irreducible links, describing dyadic social ties, simultaneously vary over time. We develop a general mean field theory for the Susceptible-Infected-Susceptible model and conduct an extensive numerical campaign to elucidate the role of network parameters on the average degree of the temporal network and the epidemic threshold. Specifically, we describe how the interplay between reducible and irreducible links influences the disease dynamics, offering insights towards the analysis of complex dynamical networks across science and engineering.
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Ikeda, 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.

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Kapetanaki, 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.

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Uchimura, 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.

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Li, 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.

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Hallac, 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.

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Reports on the topic "Time-varying network"

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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.

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Dew-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.

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Miller-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.

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Woods, 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.

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Gearhart, 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.

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Bowler, 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.

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Kushner, 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.

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Miles, 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.

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Abstract:
In this work multispectral reflectance images are used in conjunction with a neural network classifier for the purpose of detecting and classifying weeds under real field conditions. Multispectral reflectance images which contained different combinations of weeds and crops were taken under actual field conditions. This multispectral reflectance information was used to develop algorithms that could segment the plants from the background as well as classify them into weeds or crops. In order to segment the plants from the background the multispectrial reflectance of plants and background were studied and a relationship was derived. It was found that using a ratio of two wavelenght reflectance images (750nm and 670nm) it was possible to segment the plants from the background. Once ths was accomplished it was then possible to classify the segmented images into weed or crop by use of the neural network. The neural network developed for this work is a modification of the standard learning vector quantization algorithm. This neural network was modified by replacing the time-varying adaptation gain with a constant adaptation gain and a binary reinforcement function. This improved accuracy and training time as well as introducing several new properties such as hill climbing and momentum addition. The network was trained and tested with different wavelength combinations in order to find the best results. Finally, the results of the classifier were evaluated using a pixel based method and a block based method. In the pixel based method every single pixel is evaluated to test whether it was classified correctly or not and the best weed classification results were 81% and its associated crop classification accuracy is 57%. In the block based classification method, the image was divided into blocks and each block was evaluated to determine whether they contained weeds or not. Different block sizes and thesholds were tested. The best results for this method were 97% for a block size of 8 inches and a pixel threshold of 60. A simulation model was developed to 1) quantify the effectiveness of a site-specific sprayer, 2) evaluate influence of diffeent design parameters on efficiency of the site-specific sprayer. In each iteration of this model, infected areas (weed patches) in the field were randomly generated and the amount of required herbicides for spraying these areas were calculated. The effectiveness of the sprayer was estimated for different stain sizes, nozzle types (conic and flat), nozzle sizes and stain detection levels of the identification system. Simulation results indicated that the flat nozzle is much more effective as compared to the conic nozzle and its relative efficiency is greater for small nozzle sizes. By using a site-specific sprayer, the average ratio between the spraying areas and the stain areas is about 1.1 to 1.8 which can save up to 92% of herbicides, especially when the proportion of the stain areas is small.
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Bielinskyi, 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.

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The focus of this study to measure the varying irreversibility of stock markets. A fundamental idea of this study is that financial systems are complex and nonlinear systems that are presented to be non-Gaussian fractal and chaotic. Their complexity and different aspects of nonlinear properties, such as time irreversibility, vary over time and for a long-range of scales. Therefore, our work presents approaches to measure the complexity and irreversibility of the time series. To the presented methods we include Guzik’s index, Porta’s index, Costa’s index, based on complex networks measures, Multiscale time irreversibility index and based on permutation patterns measures. Our study presents that the corresponding measures can be used as indicators or indicator-precursors of crisis states in stock markets.
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Event-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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Because autonomous vehicles (AVs) equipped with active front steering have the features of time varying, uncertainties, high rate of fault, and high burden on the in-vehicle networks, this article studies the adaptive robust control problem for improving lateral stability in steer-by-wire (SBW) vehicles in the presence of abrupt nonlinear faults. First, an upper-level robust H∞ controller is designed to obtain the desired front-wheel steering angle for driving both the yaw rate and the sideslip angle to reach their correct values. Takagi-Sugeno (T-S) fuzzy modeling method, which has shown the extraordinary ability in coping with the issue of nonlinear, is applied to deal with the challenge of the changing longitudinal velocity. The output of the upper controller can be calculated by a parallel distributed compensation (PDC) scheme. Then an event-triggered adaptive fault-tolerant lower controller (ET-AFTC) is proposed to drive the whole SBW system driving the desired steering angle offered by the upper controller with fewer communication resources and strong robustness. By employing a backstepping technique, the tracking performance is improved. The dynamic surface control (DSC) approach is used to avoid the problem of repeated differentiations, and Nussbaum function is adopted to overcome the difficulty of unknown nonlinear control gain. Both the stability of the upper and lower controllers can be guaranteed by Lyapunov functions. Finally, the simulations of Matlab/Simulink are given to show that the proposed control strategy is effectively able to deal with the abrupt nonlinear fault via less communication resources and perform better in ensuring the yaw stability of the vehicle.
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