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The task of identifying an unknown dynamic system is made easier with prior knowledge on its behaviour. Using a frequency domain approach, the non-parametric maximum likelihood estimator of the system function, associated with the time-dependent impulse response of a time-varying system, is constructed. This is accomplished by use of a simple linear least(More)
—This paper presents a nonparametric method for detecting and quantifying the influence of time-variation in frequency response function (FRF) 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(More)
This paper proposes a methodology to easily extract some valuable non-parametric 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 non-parametric idea of the speed of variation of the instantaneous(More)
—Recently a method has been developed for detecting and quantifying the time-variation in frequency response function (FRF) measurements using arbitrary excitations [1]. The following basic assumptions have been made: (i) the input is known exactly (generalized output error stochastic framework), and (ii) the time-variant system operates in open loop. The(More)