Research at the department ELEC

"ELEC" stands for "Fundamental Electricity and Instrumentation" (in dutch: "Algemene Elektriciteit en Instrumentatie") and the name corresponds with the educational and research tasks and objectives of the department. The main research activity of the department is the development of new measurement techniques using advanced signal processing methods, embedded in an identification framework. There are no formal research groups in the department ELEC. There are 3 research teams that cooperate intensively with each other. Team A: Data driven modeling (Rik Pintelon) Team B: Applied signal processing for engineering, telecommunications and Microwave systems (Gerd Vandersteen, Yves Rolain and Leo Van Biesen) Team C: Structured low-rank approximation (Ivan Markovsky)

Overview Research Topics

The long term objective of the department is the realization of the IMMI project (Interpretation by Measuring, Modelling and Identification), since 1989. Beside this main project, which covers a broad spectrum of several related activities, also some other independent research topics are at stake.

Unfalsified LTI models with bounded complexity in the behavioral framework

The notion of the most powerful unfalsified model (MPUM), introduced by Jan C. Willems in the late 1980s, led to a growing interest in exact model identification by researchers from the systems and control community. Willems defined the MPUM for a noise-free infinite time series as the least...

Data-driven linear quadratic tracking control

Data-driven control is an alternative to the classical model-based control paradigm that does not identify a model of the plant. In this paper, we show that linear quadratic tracking control is equivalent to errors-in-variables Kalman filtering. Alternatively, data-driven tracking control is...

Multi-channel sum-of-exponentials common dynamics estimation

Estimation of common dynamics among several observed signals occurs in signal processing, system theory, and computer algebra problems. In this paper, we propose subspace methods for common linear time-invariant dynamics detection and estimation. First, we consider the deterministic problem of...

Identifying Reflections in High Frequency Structures

The goal of this work is to improve the modeling of Lumped Distributed Structures (LDSs) by obtaining a sensible aaccuracy with a reasonably low number of model parameters while identifying the reflections present.

Developing wave-based calibration for vector network analyzers

Current state-of-the-art in RF calibration

Calibration is an essential part of any RF, microwave and millimeter wave measurement process. The accuracy of a bare-bones high-frequency measurement instrument is jeopardized by the influences of non-idealities, cabling and instrument drift....

Data-driven signal processing using the nuclear norm heuristic

Applications in signal processing and control theory are typically model-based and proceed in two steps. In the 'modeling' step, a mathematical model is built from the measured noisy data. In the 'design' step, the model is used to solve a specific application problem. In this project, we will...


Back to top