In most social, information, and collaboration systems the complex activity of agents generates rapidly evolving time-varying networks. Temporal changes in the network structure and the dynamical processes occurring on its fabric are usually coupled in ways that still challenge our mathematical or computational modelling. Here we analyse a mobile call dataset describing the activity of millions...

in this paper, an adaptive fuzzy control scheme is proposed for a class of perturbed strict-feedback nonlinear systems with unknown discrete and distributed time-varying delays, and the proposed design method does not require a priori knowledge of the signs of the control gains.based on the backstepping technique, the adaptive fuzzy controller is constructed. the main contributions of the paper...

in this paper, global robust stability of stochastic impulsive recurrent neural networks with time-varyingdelays which are represented by the takagi-sugeno (t-s) fuzzy models is considered. a novel linear matrix inequality (lmi)-based stability criterion is obtained by using lyapunov functional theory to guarantee the asymptotic stability of uncertain fuzzy stochastic impulsive recurrent neural...

in this study, 3 models of time-varying parameters (tvp), dynamic model selection (dms) and dynamic model averaging (dma) and a comparison with the ordinary least squares (ols) method in matlab in the time period 2003-2013 (with data on a monthly basis) are discussed. in the present study, the variables of unofficial exchange rate changes, interest rate changes and inflation in oil price foreca...

this article presents a fuzzy robust mixed - sensitivity gain - scheduled h controller based on the loop -shaping methodology for a class of mimo uncertain nonlinear time - varying systems. in order to design this controller, the nonlinear parameter - dependent plant is first modeled as a set of linear subsystems by takagi and sugeno’s (t - s) fuzzy approach. both loop - shaping methodology and...