Searched for: department%3A%22Intelligent%255C+Systems%22
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Van de Bovenkamp, R. (author), Van Mieghem, P. (author)
The survival time T is the longest time that a virus, a meme, or a failure can propagate in a network. Using the hitting time of the absorbing state in an uniformized embedded Markov chain of the continuous-time susceptible-infected-susceptible (SIS) Markov process, we derive an exact expression for the average survival time E[T ] of a virus in...
journal article 2015
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Van Mieghem, P.F.A. (author), Van de Bovenkamp, R. (author)
Mean-field approximations (MFAs) are frequently used in physics. When a process (such as an epidemic or a synchronization) on a network is approximated by MFA, a major hurdle is the determination of those graphs for which MFA is reasonably accurate. Here, we present an accuracy criterion for Markovian susceptible-infected-susceptible (SIS)...
journal article 2015
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Van de Bovenkamp, R. (author)
Local interactions on a graph will lead to global dynamic behaviour. In this thesis we focus on two types of dynamic processes on graphs: the Susceptible-Infected-Susceptilbe (SIS) virus spreading model, and gossip style epidemic algorithms. The largest part of this thesis is devoted to the SIS model. We first introduce the SIS model in chapter...
doctoral thesis 2015
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Guo, D. (author), Trajanovski, S. (author), Van de Bovenkamp, R. (author), Wang, H. (author), Van Mieghem, P.F.A. (author)
The interplay between disease dynamics on a network and the dynamics of the structure of that network characterizes many real-world systems of contacts. A continuous-time adaptive susceptible-infectious-susceptible (ASIS) model is introduced in order to investigate this interaction, where a susceptible node avoids infections by breaking its...
journal article 2013
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Cator, E. (author), Van de Bovenkamp, R. (author), Van Mieghem, P.F.A. (author)
The classical, continuous-time susceptible-infected-susceptible (SIS) Markov epidemic model on an arbitrary network is extended to incorporate infection and curing or recovery times each characterized by a general distribution (rather than an exponential distribution as in Markov processes). This extension, called the generalized SIS (GSIS)...
journal article 2013
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Van Mieghem, P.F.A. (author), Van de Bovenkamp, R. (author)
Most studies on susceptible-infected-susceptible epidemics in networks implicitly assume Markovian behavior: the time to infect a direct neighbor is exponentially distributed. Much effort so far has been devoted to characterize and precisely compute the epidemic threshold in susceptible-infected-susceptible Markovian epidemics on networks. Here,...
journal article 2013
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