Tomás Hrúz

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We study stochastic processes that generate nongrowing complex networks without self-loops and multiple edges (simple graphs). The work concentrates on understanding and formulation of constraints which keep the rewiring stochastic processes within the class of simple graphs. To formulate these constraints a different concept of wedge distribution (paths of(More)
We present an experimental work and a concept based on complete, edge-colored graphs which goes towards the development of a non-growing scale-free process which would lack the disadvantages of the processes known so far i.e. a process that would i) stay in the class of simple graphs, ii) reach a scale-free degree distribution independently of the initial(More)
The main goal of our paper is to study the regularization problems which occur in predictive control of systems with severely ill-posed inverse model. We propose a new formulation of predictive control where the future controls are obtained as a solution of certain ill-posed inverse problem. This formulation leads to a possibility of closed loop on-line(More)
The main goal of this paper is to study the regulariza tion problems which occur in predictive control of systems with severely ill posed inverse model We propose a new formulation of predictive control where the future controls are obtained as a solution of certain ill posed inverse problem This formulation leads to a possibility of closed loop on line(More)
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