Control systems are usually modeled by differential equations describing how physical phenomena can be influenced by certain control parameters or inputs. Although these models ar...
Abstract. Gaussian process models provide a probabilistic non-parametric modelling approach for black-box identification of nonlinear dynamic systems. The Gaussian processes can h...
This tutorial reports on the use of nonlinear dynamics in several different models of neural systems. We discuss a number of distinct approaches to neural information processing ba...
This paper presents Lyapunov functions for proving stability of steady gliding motions for vehicles with hydrodynamic or aerodynamic forces and moments. Because of lifting forces ...
Abstract— Symbolic models are abstract descriptions of continuous systems in which symbols represent aggregates of continuous states. In the last few years there has been a growi...