The Experts below are selected from a list of 147 Experts worldwide ranked by ideXlab platform

R Pintelon - One of the best experts on this subject based on the ideXlab platform.

  • detection and quantification of the influence of time variation in frequency response function measurements using arbitrary excitations
    IEEE Transactions on Instrumentation and Measurement, 2012
    Co-Authors: R Pintelon, Ebrahim Louarroudi, John Lataire
    Abstract:

    This paper presents a nonparametric method for detecting and quantifying the influence of time variation in frequency response function measurements. The method is based on the estimation of the best linear time-invariant (BLTI) approximation of a linear time-variant (LTV) system from known input, noisy output data. The key idea consists in reformulating the single-input, single-output time-variant problem as a multiple-input, single-output time-invariant problem. In addition to the BLTI approximation of the LTV system, the contribution of the Disturbing Noise, the leakage error, and the time-varying effects at the output is also quantified. As such, the approximation error of the time-invariant framework is known.

  • estimating a nonparametric colored Noise model for linear slowly time varying systems
    IEEE Transactions on Instrumentation and Measurement, 2009
    Co-Authors: John Lataire, R Pintelon
    Abstract:

    This paper proposes a methodology to easily extract some valuable nonparametric information on linear slowly time-varying systems, which have been excited by multisines. More specifically, it is first explained how time-varying systems behave when excited by multisines and how a rough nonparametric idea of the speed of variation of the instantaneous frequency response function is estimated. Second, a nonparametric model of the Disturbing colored Noise on the measured input and output signals is estimated. The methodology circumvents the need for repeated experiments, which are, for time-varying systems, usually difficult to perform. The estimation of the Disturbing Noise is mandatory when identifying dynamic systems within an errors-in-variables framework. The estimated Noise model is intended for system identification performed in the frequency domain, where a nonparametric Noise model is easily implemented. The Noise model is estimated independently of the parameters of the time-varying system under consideration. The estimate of the speed of variation of the instantaneous frequency response function gives some insight into the measured system. It might actually provide an idea of which poles or zeros are actually moving and which are not.

  • variance analysis of frequency response function measurements using periodic excitations
    IEEE Transactions on Instrumentation and Measurement, 2005
    Co-Authors: T Dhaene, Johan Schoukens, R Pintelon, E Van Gheem
    Abstract:

    The influence of Disturbing Noise and nonlinear distortions on frequency response function measurements using periodic excitations has been studied in detail in the literature. A variance analysis method has been developed that allows one to detect and quantify the nonlinear distortions and the Disturbing Noise. In this paper, the variance analysis is generalized to detect and quantify the following nonstationary disturbances: 1) nonsynchronous periodic signals, for example, the 50 Hz mains and its harmonics, and 2) nonstationary behavior of the device under test, for example, phase or frequency modulation.

  • variance analysis of frequency response function measurements using periodic excitations
    Instrumentation and Measurement Technology Conference, 2004
    Co-Authors: T Dhaene, Johan Schoukens, R Pintelon, E Van Gheem
    Abstract:

    The influence of Disturbing Noise and non-linear distortions on frequency response function (FRF) measurements using periodic excitations has been studied in detail in the literature. A variance analysis method has been developed that allows to detect and quantify the non-linear distortions and the Disturbing Noise. In this paper the variance analysis is generalised to detect and quantify the following non-stationary disturbances: (i) non-synchronous periodic signals, for example the 50Hz mains and its harmonics, and (ii) non-stationary behaviour of the device under test, for example phase or frequency modulation.

  • frequency domain subspace system identification using non parametric Noise models
    Automatica, 2002
    Co-Authors: R Pintelon
    Abstract:

    In the general case of non-uniformly spaced frequency-domain data and/or arbitrarily coloured Disturbing Noise, the frequency-domain subspace identification algorithms described in McKelvey, Akcay, and Ljung (IEEE Trans. Automatic Control 41(7) (1996) 960) and Van Overschee and De Moor (Signal Processing 52(2) (1996) 179) are consistent only if the covariance matrix of the Disturbing Noise is known. This paper studies the asymptotic properties (strong convergence, convergence rate, asymptotic normality, strong consistency and loss in efficiency) of these algorithms when the true Noise covariance matrix is replaced by the sample Noise covariance matrix obtained from a small number of independent repeated experiments. As an additional result the strong convergence (in case of model errors), the convergence rate and the asymptotic normality of the subspace algorithms with known Noise covariance matrix follows.

Johan Schoukens - One of the best experts on this subject based on the ideXlab platform.

  • variance analysis of frequency response function measurements using periodic excitations
    IEEE Transactions on Instrumentation and Measurement, 2005
    Co-Authors: T Dhaene, Johan Schoukens, R Pintelon, E Van Gheem
    Abstract:

    The influence of Disturbing Noise and nonlinear distortions on frequency response function measurements using periodic excitations has been studied in detail in the literature. A variance analysis method has been developed that allows one to detect and quantify the nonlinear distortions and the Disturbing Noise. In this paper, the variance analysis is generalized to detect and quantify the following nonstationary disturbances: 1) nonsynchronous periodic signals, for example, the 50 Hz mains and its harmonics, and 2) nonstationary behavior of the device under test, for example, phase or frequency modulation.

  • variance analysis of frequency response function measurements using periodic excitations
    Instrumentation and Measurement Technology Conference, 2004
    Co-Authors: T Dhaene, Johan Schoukens, R Pintelon, E Van Gheem
    Abstract:

    The influence of Disturbing Noise and non-linear distortions on frequency response function (FRF) measurements using periodic excitations has been studied in detail in the literature. A variance analysis method has been developed that allows to detect and quantify the non-linear distortions and the Disturbing Noise. In this paper the variance analysis is generalised to detect and quantify the following non-stationary disturbances: (i) non-synchronous periodic signals, for example the 50Hz mains and its harmonics, and (ii) non-stationary behaviour of the device under test, for example phase or frequency modulation.

  • frequency domain system identification using non parametric Noise models estimated from a small number of data sets
    Automatica, 1997
    Co-Authors: Johan Schoukens, R Pintelon, Gerd Vandersteen, Patrick Guillaume
    Abstract:

    Abstract This paper discusses the problem of identifying a linear system from the frequency data when the measurements of the input and the output signals are both disturbed with Noise. A typical example of such a problem is the identification of a system in a feedback loop. It is known that this problem can be solved using errors-in-varaibles methods if the covariance matrices of the Disturbing Noise (on input and output measurements) are a priori known. It is shown that the exact covariance matrices can be replaced by the sample covariance matrices: the system can be identified from the sample means and sample covariance matrices calculated from a (small) number M of independently repeated experiments. It is shown that under these conditions the estimates are still strongly consistent for an increasing number of data points N in each experiment ( N → ∞) if M ≥ 4. The loss in efficiency is quantified ( M ≥ 6), and the expected value of the cost function ( M ≥ 4) and its variance ( M ≥ 6) are calculated.

Wooihaw Tan - One of the best experts on this subject based on the ideXlab platform.

  • identification of a multivariable nonlinear and time varying mist reactor system
    Control Engineering Practice, 2017
    Co-Authors: C L Cham, Ai Hui Tan, Wooihaw Tan
    Abstract:

    Abstract This paper considers the identification of a multivariable nonlinear and time-varying mist reactor system which presents an important system in the industry for applications in cell culture. A systematic approach is formulated for characterizing the linear dynamics, nonlinear distortion, Disturbing Noise and time variation. The best time-invariant approximation is introduced as part of the methodology in the proposed approach. By incorporating significant nonlinear terms into the model, the main source of disturbance can be determined with greater confidence. The power at the different harmonics is further capitalized upon in deriving an indicator for the relative variance of the time-varying delay.

Patrick Guillaume - One of the best experts on this subject based on the ideXlab platform.

  • frequency domain system identification using non parametric Noise models estimated from a small number of data sets
    Automatica, 1997
    Co-Authors: Johan Schoukens, R Pintelon, Gerd Vandersteen, Patrick Guillaume
    Abstract:

    Abstract This paper discusses the problem of identifying a linear system from the frequency data when the measurements of the input and the output signals are both disturbed with Noise. A typical example of such a problem is the identification of a system in a feedback loop. It is known that this problem can be solved using errors-in-varaibles methods if the covariance matrices of the Disturbing Noise (on input and output measurements) are a priori known. It is shown that the exact covariance matrices can be replaced by the sample covariance matrices: the system can be identified from the sample means and sample covariance matrices calculated from a (small) number M of independently repeated experiments. It is shown that under these conditions the estimates are still strongly consistent for an increasing number of data points N in each experiment ( N → ∞) if M ≥ 4. The loss in efficiency is quantified ( M ≥ 6), and the expected value of the cost function ( M ≥ 4) and its variance ( M ≥ 6) are calculated.

Felipe Ordunabustamante - One of the best experts on this subject based on the ideXlab platform.

  • improving speech intelligibility for binaural voice transmission under Disturbing Noise and reverberation using virtual speaker lateralization
    Journal of Applied Research and Technology, 2015
    Co-Authors: A Padilla L Ortiz, Felipe Ordunabustamante
    Abstract:

    Subjective speech intelligibility tests were carried out in order to investigate strategies to improve speech intelligibility in binaural voice transmission when listening from different azimuth angles under adverse listening conditions. Phonetically balanced bi-syllable meaningful words in Spanish were used as speech material. The speech signal was played back through headphones, undisturbed, and also with the addition of high levels of Disturbing Noise or reverberation, with a signal to Noise ratio of SNR = –10 dB and a reverberation time of T60 = 10 s. Speech samples were contaminated with interaurally uncorrelated Noise and interaurally correlated reverberation, which previous studies have shown the more adverse. Results show that, for speech contaminated with interaurally uncorrelated Noise, intelligibility scores improve for azimuth angles around ±30° over speech intelligibility at 0°. On the other hand, for interaurally correlated reverberation, binaural speech intelligibility reduces when listening at azimuth angles around ±30°, in comparison with listening at 0° or azimuth angles around ±60°. All Rights Reserved © 2015 Universidad Nacional Autonoma de Mexico, Centro de Ciencias Aplicadas y Desarrollo Tecnologico. This is an open access item distributed under the Creative Commons CC License BY-NC-ND 4.0.

  • binaural speech intelligibility and interaural cross correlation under Disturbing Noise and reverberation
    Journal of Applied Research and Technology, 2012
    Co-Authors: A L Padillaortiz, Felipe Ordunabustamante
    Abstract:

    Subjective tests were carried out in order to investigate speech intelligibility, and the possible relative improvements that can be obtained in practical applications to acoustic communication systems, for different forms of presentation through headphones: monaural, monophonic, binaural at 0o (in front of the listener) and binaural at ±30o (right or left, relative to the listener), played back undisturbed, and also with the addition of extreme levels of Disturbing Noise and reverberation, with a signal to Noise ratio of