We develop a new algorithm, based on EM, for learning the Linear Dynamical System model. Called the method of Approximated Second-Order Statistics (ASOS) our approach achieves dra...
This paper introduces a simple yete ective method for using causal domain knowledge for learning to control dynamic systems. Elementary qualitative causal dependencies of the domai...
In this paper we analyze a nonlocal reaction-diffusion model which arises from the modeling of competition of phytoplankton species with incomplete mixing in a water column. The no...
—Approximate Dynamic Inversion (ADI) has been established as a method to control minimum-phase, nonaffine-incontrol systems. Previous results have shown that for single-input no...
—Networks of coupled dynamical systems exhibit many interesting behaviours such as spatio-temporal chaos, pattern formation and synchronization. Such networks can be used to mode...