Asynchronous hybrid event- and time-triggered control of heterogeneous networks with communication time delays.

This paper addresses the asynchronous leader-following consensus problem for networked double-integrator systems. In practical engineering contexts, there are three key factors that must be considered significantly: (1) asynchronous hybrid event- and time-triggered control, where asynchrony affects event detection, event-triggered processes, and controller updates; (2) heterogeneous networks, wherein position and velocity information are governed by distinct, independent graphs; and (3) communication time delays arising from limited bandwidth and long-distance transmission. Due to the independence of these heterogeneous networks, edge events related to position and velocity information are defined separately.

Parameter inference in small world network disease models with approximate Bayesian Computational methods.

Small world network models have been effective in capturing the variable behaviour of reported case data of the SARS coronavirus outbreak in Hong Kong during 2003. Simulations of these models have previously been realized using informed "guesses" of the proposed model parameters and tested for consistency with the reported data by surrogate analysis. In this paper we attempt to provide statistically rigorous parameter distributions using Approximate Bayesian Computation sampling methods.