Showing papers by "Johan Schoukens published in 2006"
TL;DR: The Frequency Domain System Identification Toolbox has been extended with analysis tools of nonlinear system behaviour, which means model verification becomes possible even if nonlinear error terms excess linear additive noise.
19 citations
24 Apr 2006
TL;DR: A method based on the concept of filtered band limited white noise is introduced, an in depth analysis of the basic assumptions made by the different approaches are made, and the pros and cons of each method are discussed.
Abstract: Most stochastic processes in engineering applications have an intrinsic continuous-time nature. Think, for example, of the noise generated by resistors and semi-conductor devices. A few methods exist that identify continuous-time noise models from sampled data. In this paper we introduce a new method based on the concept of filtered band limited white noise, make an in depth analysis of the basic assumptions made by the different approaches, and discuss the pros and cons of each method. The new method is particularly highlighted and illustrated on real measurements.
13 citations
24 Apr 2006
TL;DR: In this paper, a novel method for designing filters generating the discrete-time analytic signal is proposed, which relies on the rotation of the pole-zero plot of a low-pass filter.
Abstract: In this paper, a novel method for designing filters generating the discrete-time analytic signal is proposed. The technique relies on the rotation of the pole-zero plot of a low-pass filter. As a consequence, the classical design methods can be reused. This method is compared to a direct filter design approach.
6 citations
TL;DR: In this paper, the authors investigated the measurement errors involved in estimating frequency response functions from weighted overlapped segment averaging, a technique that has become a standard in modern data analysers due to its computational advantages.
4 citations
24 Apr 2006
TL;DR: A method to extract a non-parametric noise model starting from periodic data with a small number of measured periods with overlapping windows is proposed.
Abstract: In this paper we propose a method to extract a non-parametric noise model starting from periodic data with a small number of measured periods. Overlapping windows are used to avoid singular results. A full theoretic analysis is made.
3 citations
TL;DR: In this paper, a simple automatic method to suppress system transients and unmodelled dynamics during variance analysis is proposed, without the need of separate observation noise analysis or of full-blown nonlinear analysis.
1 citations
29 Mar 2006
TL;DR: The main result is that a Half-sine or Diff window with 67% overlap achieves the best compromise to reduce leakage errors, and this is independently of the system frequency response function.
Abstract: This paper investigates the measurement errors involved in estimating frequency response functions from weighted overlapped segment averaging, a technique that has become a standard in modern data analysers due to its computational advantages. A particular attention is paid to leakage errors, for which this technique has been frequently criticised. Our main result is that a Half-sine or Diff window with 67% overlap achieves the best compromise to reduce leakage errors, and this is independently of the system frequency response function. This conclusion is to be contrasted with the customary habit of using a Hanning window with 50% overlap.