Publications by Zlatić V.
http://www.focproject.eu/publications/58
enRobustness and assortativity for Diffusion-like Processes in
Scale-Free Networks
http://www.focproject.eu/publications/robustness-and-assortativity-diffusion-processes-scale-free-networks-0
<div class="field field-name-body field-type-text-with-summary field-label-hidden"><div class="field-items"><div class="field-item even" property="content:encoded"><p>By analysing the diffusive dynamics of epidemics and of distress in complex networks, we study the effect of the assortativity on the robustness of the networks. We first determine by spectral analysis the thresholds above which epidemics/failures can spread; we then calculate the slowest diffusional times. Our results shows that disassortative networks exhibit a higher epidemiological threshold and are therefore easier to immunize, while in assortative networks there is a longer time for intervention before epidemic/failure spreads.</p></div></div></div>Tue, 16 Oct 2012 15:05:53 +000022873 at http://www.focproject.euNetworks with arbitrary edges multiplicities
http://www.focproject.eu/publications/networks-arbitrary-edges-multiplicities-0
<div class="field field-name-body field-type-text-with-summary field-label-hidden"><div class="field-items"><div class="field-item even" property="content:encoded"><p>One of the main characteristics of real-world networks is their large clustering. Clustering is one aspect of a more general but much less studied structural organization of networks, i.e. edge multiplicity, defined as the number of triangles in which edges, rather than vertices, participate. Here we show that the multiplicity distribution of real networks is in many cases scale free, and in general very broad.</p></div></div></div>Tue, 16 Oct 2012 15:05:53 +000022874 at http://www.focproject.euTopologically biased random walk and community finding in networks
http://www.focproject.eu/publications/topologically-biased-random-walk-and-community-finding-networks
<div class="field field-name-body field-type-text-with-summary field-label-hidden"><div class="field-items"><div class="field-item even" property="content:encoded"><p>We present an approach of topology biased random walks for undirected networks. We focus on a one-parameter family of biases, and by using a formal analogy with perturbation theory in quantum mechanics we investigate the features of biased random walks. This analogy is extended through the use of parametric equations of motion to study the features of random walks vs parameter values. Furthermore, we show an analysis of the spectral gap maximum associated with the value of the second eigenvalue of the transition matrix related to the relaxation rate to the stationary state.</p></div></div></div>Tue, 16 Oct 2012 15:05:53 +000022879 at http://www.focproject.eu