This paper adresses the variance quantification problem for system identification based on the prediction error framework. The role of input and model class selection for the auto-...
— This paper analyzes two classes of consensus algorithms in presence of bounded measurement errors. The protocols taken into account adopt an updating rule based either on const...
The study focuses on a class of discrete-time multi-agent systems modelling opinion dynamics with decaying confidence. Essentially, we propose an agreement protocol that impose a p...
Model selection by the predictive least squares (PLS) principle has been thoroughly studied in the context of regression model selection and autoregressive (AR) model order estima...
This paper studies a nonlinear vector precoding scheme which inverts the wireless multiple-input multiple-output (MIMO) channel at the transmitter so that simple symbol-bysymbol de...