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.

Learning Kalman filtering with Lego mindstorms

Research shows that, in learning science and engineering, guided project work leads to deeper understanding of theoretical concepts (as well as acquisition of hands-on skills) than the classical approach of textbook reading and attending lectures. In an approach to education based on project...

Using structured low-rank approximation for sparse signal recovery

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...

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...

Nonparametric identification of linear dynamic errors-in-variables systems

The present work handles the nonparametric identification of linear dynamic systems within an errors-in-variables framework, where the input is arbitrary, and both the input and output disturbing noises are white with unknown variances. Using the property that the frequency response function and...

Carrier aggregation intermodulation distortions in Advanced Systems

Achieving greater throughput requires increasing bandwidth. However, due to frequency’s scarcity, the necessary bandwidth may not be available in one contiguous band. LTE Advanced use multiple bands for one user: that is carrier aggregation [1]. However power amplifier’s efficiency is only...

Identification of time-varying biomechanical systems

This project aims at extracting models of human joints in a data driven manner. This is done in collaboration with the biomechanics group at the TU Delft, where experimental setups have been instrumented to apply force and position disturbances to joints (ankle, wrist and shoulder). Based on...

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