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.
A Novel Wave-Based Stochastic Calibration Framework for High- Frequency Measurement and Modeling
Calibration is essential to any high-frequency measurement. Over the last 50 years, the calibration framework has remained one of S-parameters and deterministic approaches, while applications have undergone a metamorphosis. The introduction of 5G telecom will call for a fast, accurate, and...
A gradient system approach for Hankel structured low-rank approximation
A Hankel matrix H is a structured matrix whose entry on the i-th row and the j-th column depends only on the sum i + j. Hankel matrices can be associated in a natural way to vectors or time series.
Identification of dynamic errors-in-variables systems with arbitrary input and colored noise
We studied the linear dynamic errors-in-variables (EIV) problem in a fairly general condition where the input–output disturbing noises are colored and the input is quasi-stationary. A novel formulation of the extended frequency domain maximum likelihood (ML) estimator is developed which reduces...
Augmented blended learning by empowering blended teaching with entropy-based learning analytics
The research aims for augmented blended learning by strengthening the blended learning strategy with quantitatively measured learning analytic.
InVentiVe Interreg project
The aim of the InVentiVE project is to...
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...
Linear Time-Varying System Identification in the Presence of Nonlinear Distortions
In this research we consider time-varying systems that are nonlinear to some extent. The output spectrum of such a system, when excited by a multisine, consists of skirts around the excited frequencies, but also could have nonlinear contributions at multiples of the multisine’s fundamental...
Identification of nonlinear continuous-time systems from noisy input/output observations
The identification and control of LTI systems (linear time-invariant systems) is well established among engineers. So, there is no surprise if one tries to model a nonlinear system with a bunch of LTI systems. There are various ways to do so but maybe LPV (linear parameter varying) modeling...
Estimation of respiratory impedance at low frequencies using the forced oscillation technique
The forced oscillation technique (FOT) is a non-invasive measurement technique to characterize the impedance of a respiratory system (Zrs). Zrs is defined as a frequency dependent ratio of pressure at the airway opening (pao) to air flow (qe) induced by Zrs.
Realization and identification of autonomous Wiener systems via low-rank approximation
Wiener systems are nonlinear dynamical systems, consisting of a linear dynamical system and a static nonlinear system in a series connection. Existing results for analysis and identification of Wiener systems assume zero initial conditions. In this paper, we consider the response of a Wiener...
Applications of polynomial common factor computation in signal processing and systems theory
We consider the problem of computing the greatest common divisor of a set of univariate polynomials and present applications of this problem in system theory and signal processing. One application is blind system identification: given the responses of a system to unknown inputs, find the system...
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...
Carrier aggregation intermodulation distortions in Advanced Systems
Achieving greater throughput in telecommunications requires increasing bandwidth. However, due to scarcity in carrier frequencies, the required bandwidth may not be available in a contiguous band. LTE Advanced uses multiple bands for one single user, which is known as carrier aggregation [1...
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...