We provide an algorithm to generate trajectories of sparse stochastic processes that are solutions of linear ordinary differential equations driven by Levy white noises. A recent paper showed that these processes are limits in law of generalized compound-P ...
The macroscopic dynamics of large populations of neurons can be mathematically analyzed using low-dimensional firing-rate or neural-mass models. However, these models fail to capture spike synchronization effects and nonstationary responses of the populati ...
We investigate a non-Markovian analogue of the Harris contact process in Z(d): an individual is attached to each site x is an element of Z(d), and it can be infected or healthy; the infection propagates to healthy neighbours just as in the usual contact pr ...
Though the following topics seem unlinked, most of the tools used in this thesis are related to random walks and renewal theory. After introducing the voter model, we consider the parabolic Anderson model with the voter model as catalyst. In GÄRTNER, DEN H ...
We study the dynamics of systems with deterministic trajectories randomly forced by instantaneous discontinuous jumps occurring according to two different compound Poisson processes. One process, with constant frequency, causes instantaneous positive rando ...
Sequences of events in noise-driven excitable systems with slow variables often show serial correlations among their intervals of events. Here, we employ a master equation for generalized non-renewal processes to calculate the interval and count statistics ...
Traditionally, the bursty nature of data sources is not taken in consideration by information theory. Random arrival times typically are assumed to be smoothed out by appropriate source coding, rendering any meaningful analysis of the end-to-end delay impo ...