Abstract-- We consider optimal experiment design for parametric prediction error system identification of linear timeinvariant systems in closed loop. The optimisation is performed...
Abstract— One of the major challenges in both action generation for robotics and in the understanding of human motor control is to learn the “building blocks of movement genera...
Image segmentation techniques are predominately based on parameter-laden optimization processes. The segmentation objective function traditionally involves parameters (i.e. weights...
This paper presents an approach to learning an optimal behavioral parameterization in the framework of a Case-Based Reasoning methodology for autonomous navigation tasks. It is ba...
The utility of simulations and analysis heavily relies on good models of network traffic. While network traffic constantly changing over time, existing approaches typically take y...