September 2, 2017

Download Advances in Network Analysis and its Applications by Hamed Amini, Andreea Minca (auth.), Evangelos Kranakis PDF

By Hamed Amini, Andreea Minca (auth.), Evangelos Kranakis (eds.)

ISBN-10: 3642309038

ISBN-13: 9783642309038

As good as highlighting possibly valuable purposes for community research, this quantity identifies new pursuits for mathematical examine that promise to supply insights into community structures idea in addition to facilitating the cross-fertilization of rules among sectors. targeting monetary, safeguard and social features of networking, the amount provides to the starting to be physique of facts exhibiting that community research has functions to transportation, verbal exchange, healthiness, finance, and social coverage extra largely. It offers strong types for realizing the habit of complicated platforms that, in flip, will effect quite a few state-of-the-art sectors in technology and engineering, reminiscent of instant verbal exchange, community defense, allotted computing and social networking, monetary research, and cyber warfare.

The quantity deals an insider’s view of state of the art study in community platforms, together with methodologies with titanic power for interdisciplinary software. The participants have all awarded fabric at a chain of workshops equipped on behalf of Canada’s MITACS initiative, which cash initiatives and research provides in ‘mathematics for info expertise and complicated systems’. those complaints comprise papers from workshops on monetary networks, community safeguard and cryptography, and social networks. MITACS has proven that the partially ghettoized nature of community platforms learn has ended in duplicated paintings in discrete fields, and hence this initiative has the capability to avoid wasting time and speed up the velocity of study in a few components of community platforms research.

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Extra resources for Advances in Network Analysis and its Applications

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Starting from a set of nodes initially in the state 1, other nodes switch to state 1 according to the weighted influence of their neighbors and a personal threshold. More precisely, we define the network wn on the vertex set v = {1, . . , n}, whereby wn (i, j) weighs the influence of node j on the state of node i. Each node i has a threshold qn (i) which determines its capacity to withstand the influence of other nodes. Denoting by X( j) ∈ {0, 1} the state of a node j, node i switches to state 1 the first time the following condition is met ∑ X( j)wn (i, j) > qn(i).

Federal Reserve Bank of New York Staff Reports, (338), 2008. 2. T. Adrian and H. S. Shin. The changing nature of financial intermediation and the financial crisis of 2007–2009. Annual Review of Economics, 2(1):603–618, 2010. 3. F. Allen and D. Gale. Financial contagion. Journal of Political Economy, 108(1):1–33, 2000. 4. H. Amini, R. Cont, and A. Minca. Resilience to Contagion in Financial Networks. SSRN eLibrary, 2010. 5. H. Amini, R. Cont, and A. Minca. Stress testing the resilience of financial networks.

4. The previous definition does not account directly for dependence between the weight of an edge and the node in which the edge ends, which may be unrealistic in applications. Fortunately, we can easily extend the previous model in this sense. The intuition behind our construction can be given by rephrasing the Pareto principle: 20% of the links carry 80% of the weights. Therefore, we will distinguish between two types of links, type A and type B. In applications, we will think of links of type A as those 20 H.

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