Masaki Ogura

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In this paper we study the dynamics of epidemic processes taking place in adaptive networks of arbitrary topology. We focus our study on the adaptive susceptible-infected-susceptible (ASIS) model, where healthy individuals are allowed to temporarily cut edges connecting them to infected nodes in order to prevent the spread of the infection. In this paper we(More)
This paper studies the mean stability of positive semi-Markovian jump linear systems. We show that their mean stability is characterized by the spectral radius of a matrix that is easy to compute. In deriving the condition we use a certain discretization of a semi-Markovian jump linear system that preserves stability. Also we show a characterization for the(More)
In this paper, we analyze the dynamics of spreading processes taking place over time-varying networks. A common approach to model time-varying networks is via Markovian random graph processes. This modeling approach presents the following limitation: Markovian random graphs can only replicate switching patterns with exponential inter-switching times, while(More)
We compared the phagocytosis of immune complexes (IC) and iC3b-opsonized derivatives (iC3b-IC) by human neutrophils. The phagocytosis of iC3b-IC via Fc gamma R and CR3 was much greater than that of IC via Fc gamma R alone. Adding ethanol to the cells decreased iC3b-IC phagocytosis to that of IC, which was not affected by these reagents, suggesting that the(More)
In this paper, we consider signal interpolation of discrete-time signals which are decimated nonuniformly. A conventional interpolation method is based on the sampling theorem, and the resulting system consists of an ideal filter with complex-valued coefficients. While the conventional method assumes band limitation of signals, we propose a new method by(More)
In this paper we propose a general class of models for spreading processes we call the SI∗V ∗ model. Unlike many works that consider a fixed number of compartmental states, we allow an arbitrary number of states on arbitrary graphs with heterogeneous parameters for all nodes and edges. As a result, this generalizes an extremely large number of models(More)
In this paper, we propose an optimization framework to design a network of positive linear systems whose structure switches according to a Markov process. The optimization framework herein proposed allows the network designer to optimize the coupling elements of a directed network, as well as the dynamics of the nodes in order to maximize the stabilization(More)
In this paper, we analyze the L2-gain of a class of switched linear systems under sampled-data state-feedback control. We consider switched linear systems whose switching signal is a regenerative process. Using the lifting approach and piecewise-constant approximations, we derive a sequence whose limit inferior upper-bounds the L2-gain of the closed-loop(More)