Time-varying parameter (TVP) models often assume that the TVPs evolve according to a random walk. This assumption, however, might be questionable since it implies coefficients change smoothly and in an unbounded manner. assumption is relaxed by proposing flexible law of motion for large-scale vector autoregressions (VARs). Instead imposing restrictive walk evolution latent states, hierarchical ...

In this paper, the relation between synchronization and control of chaotic nodes connected through a time–varying network is discussed. In particular, the effects of pinning control on a set of moving chaotic agents are investigated showing that the role of system parameters, like agent density, is critical in order to reach the synchronous behavior and also to control the whole network by pinn...

A novel data-driven soft sensor is designed for online product quality prediction and control performance modification in industrial units. A combined approach of time variable parameter (TVP) model, dynamic auto regressive exogenous variable (DARX) algorithm, nonlinear correlation analysis and criterion-based elimination method is introduced in this work. The soft sensor performance validation...