Publications
Applications of polynomial common factor computation in signal processing Vrije Universiteit Brussel
Using Hankel Structured Low-Rank Approximation for Sparse Signal Recovery Vrije Universiteit Brussel
Structured low-rank approximation is used in model reduction, system identification, and signal processing to find low-complexity models from data. The rank constraint imposes the condition that the approximation has bounded complexity and the optimization criterion aims to find the best match between the data—a trajectory of the system—and the approximation. In some applications, however, the data is sub-sampled from a trajectory, which ...
Predicting collisions: time-to-contact forecasting based on probabilistic segmentation and system identification Vrije Universiteit Brussel
The Time-to-contact (TTC) estimate is mainly used in robotics navigation, in order to detect potential danger with obstacles in the environment. A key aspect in a robotic system is to perform its tasks promptly. Several approaches have been proposed to estimate reliable TTC in order to avoid collisions in real-time; nevertheless they are time consuming due to a calculation of scene characteristics in every frame. This paper presents an ...
Predicting Collisions in Mobile Robot Navigation by Kalman Filter Vrije Universiteit Brussel
An ODE-based method for computing the Approximate Greatest Common Divisor of polynomials. Vrije Universiteit Brussel
Computing the greatest common divisor of a set of polynomials is a problem which plays an important role in different fields, such as linear system, control, and network theory. In practice, the polynomials are obtained through measurements and computations, so that their coefficients are inexact. This poses the problem of computing an approximate common factor. We propose an improvement and a generalization of the method recently proposed in ...
A comparison between structured low-rank approximation and correlation approach for data-driven output tracking Vrije Universiteit Brussel
Bioimpedance Parameter Estimation using Fast Spectral Measurements and Regularizaton Vrije Universiteit Brussel
Subspace identification with constraints on the impulse response Vrije Universiteit Brussel
Subspace identification methods may produce unreliable model estimates when a small number of noisy measurements are available. In such cases, the accuracy of the estimated parameters can be improved by using prior knowledge about the system. The prior knowledge considered in this paper is constraints on the impulse response. It is motivated by the availability of information about the steady-state gain, overshoot and rise time of the system, ...