Publicaties

The best linear approximation (BLA) framework
has already proven to be a valuable tool to analyze
nonlinear systems and to start the nonlinear modeling process. The existing BLA framework is limited to systems with additive (colored) noise at the output. Such a noise framework is a simplified representation of reality. Process noise can play an important role in many real-life applications.This paper generalizes the best linear ...

Estimation of periodic signals, based on quantized data, is a topic of general interest in the area of instrumentation and measurement. Although several methods are available, new applications require low-power, low-complexity, and adequate estimation accuracy. In this paper, we consider the simplest possible quantization, that is, binary quantization, and describe a technique to estimate the parameters of a sampled periodic signal, using a fast ...

This paper introduces a nonparametric, nonlinear system identification toolbox called SAMI (simplified analysis for multiple input systems) developed for industrial measurements of vibro-acoustic systems with multiple inputs. It addresses the questions related to the user-friendly (semi-)automatic processing of multiple-input, multiple-output measurements with respect to the design of an experiment and the analysis of the measured data. When the ...

Decoupling multivariate polynomials is useful for obtaining an insight into the workings of a nonlinear mapping, performing parameter reduction, or approximating nonlinear functions. Several different tensor-based approaches have been proposed independently for this task, involving different tensor representations of the functions, and ultimately leading to a canonical polyadic decomposition. We first show that the involved tensors are related ...

The goal of this article is twofold. First, nonlinear system
identification is introduced to a wide audience, guiding practicing engineers and newcomers in the field to a
sound solution of their data-driven modeling problems for
nonlinear dynamic systems. In addition, the article provides a broad perspective on the topic for researchers
who are already familiar with linear system identification
...

Many mechanical structures are nonlinear and there is no unique solution for modeling nonlinear systems. When a single-input, single-output system is excited by special signals, it is easily possible to decide whether the linear framework is still accurate enough to be used, or a nonlinear framework must be used. However, for multiple-input, multiple-output (MIMO) systems, the design of experiment is not a trivial question since the input and ...

Multivariate polynomials are omnipresent in black-box modelling. They are praised for their flexibility and ease of manipulation yet typically fall short in terms of insight and interpretability. Hence, often an alternative representation is desired. Translating the coupled polynomials into a decoupled form, containing only univariate polynomials has hence become a popular option. In this letter, two new polynomial decoupling techniques are ...

This paper presents an efficient nonparametric time-varying (TV) system identification method combined with mode tracking for Operational Modal Analysis (OMA). OMA is a special identification technique for estimating the modal properties of structures based on vibration data collected under real operating conditions and without having access to the excitation signals. The time-varying aspect refers to cases where the structural dynamic behavior ...

Applications of signal processing and control are classically model-based, involving a two-step procedure for modeling and design: first a model is built from given data, and second, the estimated model is used for filtering, estimation, or control. Both steps typically involve optimization problems, but the combination of both is not necessarily optimal, and the modeling step often ignores the ultimate design objective. Recently, data-driven ...

PurposeReliable intraoperative delineation of tumor from healthy brain tissue is essentially based on the neurosurgeon's visual aspect and tactile impression of the considered tissue, which isdue to inherent low brain consistency contrasta challenging task. Development of an intelligent artificial intraoperative tactile perception will be a relevant task to improve the safety during surgery, especially whenas for neuroendoscopytactile perception ...