The iterative method labelled Correlation-based Tuning (CbT) is considered in this paper for tuning linear time-invariant multivariable controllers. The approach allows one to tun...
We propose a framework for intensity-based registration of images by linear transformations, based on a discrete Markov Random Field (MRF) formulation. Here, the challenge arises ...
Darko Zikic, Ben Glocker, Oliver Kutter, Martin Gr...
—Structural learning with forgetting is an established method of using Laplace regularization to generate skeletal artificial neural networks. In this paper we develop a continu...
—We consider state feedback stabilization of uncertain linear systems with quantization. The plant uncertainty is dealt with by the supervisory control framework, which employs s...
This article presents and analyzes algorithms that systematically generate random Bayesian networks of varying difficulty levels, with respect to inference using tree clustering. ...