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Titlebook: Complex Systems andNetworks; Dynamics, Controls a Jinhu Lü,Xinghuo Yu,Wenwu Yu Book 2016 Springer-Verlag Berlin Heidelberg 2016 Complex Net

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Discovering Cluster Dynamics Using Kernel Spectral Methods,ph theory allows to perform insightful analysis for different kinds of data by representing the instances as nodes of a weighted network, where the weights characterize similarity between the data points. In this chapter we describe a number of algorithms to perform cluster analysis, that is finding
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Synchronization and Control of Hyper-Networks and Colored Networks,to model real large-scale systems, such as neuronal networks, metabolic networks, social relationship networks, scientific collaboration networks, and so on. Firstly, similarly to the BA scale-free network, both growth and preferential attachment mechanisms are adopted to generate some evolving hype
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New Nonlinear CPRNG Based on Tent and Logistic Maps,tic mapping, we focus first on two dimensional networks. Two coupled maps are studied: . non-alternative, and . alternative. The primary idea of the novel maps has been based on an original coupling of the tent and logistic maps to achieve excellent random properties and homogeneous/uniform/density
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