We consider state-feedback predictor-based control of networked control systems with large timevarying communication delays. We show that even a small controller-to-actuators delay uncertainty may lead to a non-small residual error in a networked control system and reveal how to analyze such systems. Then we design an event-triggered predictor-based controller with sampledmeasurements and demon...

This paper investigates the detection of communication outbreaks among a small team of actors in time-varying networks. We propose monitoring plans for known and unknown teams based on generalizations of the exponentially weighted moving average (EWMA) statistic. For unknown teams, we propose an efficient neighborhood-based search to estimate a collection of candidate teams. This procedure dram...

We study SIS epidemic spreading processes unfolding on a recent generalization of the activity-driven modeling framework. In this model of time-varying networks, each node is described by two variables: activity and attractiveness. The first describes the propensity to form connections, while the second defines the propensity to attract them. We derive analytically the epidemic threshold consid...

Recently, time-varying mesh (TVM), which is composed of a sequence of mesh models, has received considerable interest due to its new and attractive functions such as free viewpoint and interactivity. TVM captures the dynamic scene of the real world from multiple synchronized cameras. However, it is expensive and time consuming to generate a TVM sequence. In this paper, an editing system is pres...

Recently, quite a few new statistical models have been added to the variety of existing ones which try to capture the time{varying structure of nonstationary stochastic processes. Examples are numerous and can be found, e.g., in economics, speech and sound processing and the biomedical sciences. This paper gives an overview of diierent modelling approaches, e.g. locally stationary time{frequenc...

In the last decades, one of the main challenges in the study of heart rate variability (HRV) signals has been the quantification of the low-frequency (LF) and high-frequency (HF) components of the HRV spectrum during non-stationary events. At this regard, different time-frequency and time-varying approaches have been proposed with the aim to track the modification of the HRV spectra during isch...

Multiplicative error models (MEM) became a standard tool for modeling conditional durations of intraday transactions, realized volatilities and trading volumes. The parametric estimation of the corresponding multivariate model, the so-called vector MEM (VMEM), requires a specification of the joint error term distribution, which is due to the lack of multivariate distribution functions on R+ def...

Abstract—Time-frequency autoregressive moving-average (TFARMA) models have recently been introduced as parsimonious parametric models for underspread nonstationary random processes and linear time-varying (LTV) systems. In this paper, we propose linear methods for approximating an underspread LTV system by a TFARMA-type system. The linear equations obtained have Toeplitz/block-Toeplitz structur...