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Sökning: swepub > Engelska > Ljung Lennart

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31.
  • Enqvist, Martin, 1976-, et al. (författare)
  • Linear Approximations of Nonlinear FIR Systems for Separable Input Processes
  • 2005
  • Ingår i: Automatica. - Linköping : Elsevier. - 0005-1098 .- 1873-2836. ; 41:3, s. 459-473
  • Tidskriftsartikel (refereegranskat)abstract
    • Nonlinear systems can be approximated by linear time-invariant (LTI) models in-many ways. Here, LTI models that are optimal approximations in the mean-square error sense are analyzed. A necessary and sufficient condition on the input signal for the optimal LTI approximation of an arbitrary nonlinear finite impulse response (NFIR) system to be a linear finite impulse response (FIR) model is presented. This condition says that the in ut should be separable of a certain order, i.e., that certain conditional expectations should be,P linear. For the special case of Gaussian input signals, this condition is closely related to a generalized version of Bussgang's classic theorem about static nonlinearities. It is shown that this generalized theorem can be used for structure identification and for the identification of generalized Wiener-Hammerstein systems.
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32.
  • Enqvist, Martin, 1976-, et al. (författare)
  • LTI Approximations of Slightly Nonlinear Systems : Some Intriguing Examples
  • 2004
  • Ingår i: Proceedings of Reglermöte 2004. ; , s. 639-
  • Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
    • Approximations of slightly nonlinear systems with linear time-invariant (LTI) models are often used in applications. Here, LTI models that are optimal approximations in the mean-square error sense are studied. It is shown that these models can be very sensitive to small nonlinearities. Furthermore, the significance of the distribution of the input process is discussed. From the examples studied here, it seems that LTI approximations for inputs with distributions that are Gaussian or almost Gaussian are less sensitive to small nonlinearities.
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33.
  • Fnaiech, Farhat, et al. (författare)
  • On the Identification and Adaptive Control of Bilinear Systems
  • 1985
  • Ingår i: Proceedings of the JTEA'85, 6eme Journées Tunisiennes d ' Electrotechnique et d'Automatique. - Linköping : Linköping University. ; , s. Paper 19-
  • Rapport (övrigt vetenskapligt/konstnärligt)
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34.
  • Forsman, Krister, et al. (författare)
  • On the Dead-Zone in System Identification
  • 1991
  • Ingår i: Proceedings of the 9th IFAC Symposium on System Identification and System Parameter Estimation. - Linköping : Linköping University. ; , s. 1410-1414
  • Rapport (övrigt vetenskapligt/konstnärligt)abstract
    • A prediction error method for parameter estimation in a dynamical system is studied.The following problems are treated in this paper:When is the DZ estimate inconsistent, and what is the set of parameters which minimizes the criterion in the case of inconsistency?What happens to the variance of the estimate as the DZ is introduced?Does the deadzone give a better estimate than LS when there are unmodelled deterministic disturbances present?What are the relations between identification with a deadzone criterion and so called set membership identification?
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35.
  • Forssell, Urban, et al. (författare)
  • Tracking Time-Varying Systems : Revisiting Some Basic Trade-offs
  • 1997
  • Ingår i: Proceedings of the 11th IFAC Symposium on System Identification. - Linköping : Linköping University Electronic Press. - 0080425925 ; , s. 1759-1764
  • Rapport (övrigt vetenskapligt/konstnärligt)abstract
    • The trade-off between tracking ability and noise sensitivity inadaptive algorithms is a classical research topic. In this paper we will revisit some of the main results. An input/output view of the archetypical algorithms for recursive identification will be taken, thus enabling the links to H∞ and H2 norms. We will shed some light on the H∞ optimality of the LMS algorithm and also show the corresponding merits of the RLS-type algorithms. Furthermore, the role of the distribution of the noise will be illustrated.
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36.
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37.
  • Friedlander, Benjamin, et al. (författare)
  • Lattice Implementation of the Recursive Maximum Likelihood Algorithm
  • 1981
  • Ingår i: Proceedings of the 20th IEEE Conference on Decision and Control including the Symposium on Adaptive Processes. - Linköping : Linköping University. ; , s. 1083-1084
  • Rapport (övrigt vetenskapligt/konstnärligt)abstract
    • A lattice implementation of the extended least-squares algorithm was recently developed. The convergence of that algorithm depends on a positive real condition, a fact which limits its usefulness in some applications. In this note the lattice equivalent of the recursive maximum likelihood algorithm is derived. This technique does not require the positive real condition and is suitable for modeling and prediction of general ARMA time-series.
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38.
  • Gedon, Daniel, 1994-, et al. (författare)
  • Deep State Space Models for Nonlinear System Identification
  • 2021
  • Ingår i: IFAC PapersOnLine. - : Elsevier. - 2405-8963. ; , s. 481-486
  • Konferensbidrag (refereegranskat)abstract
    • Deep state space models (SSMs) are an actively researched model class for temporal models developed in the deep learning community which have a close connection to classic SSMs. The use of deep SSMs as a black-box identification model can describe a wide range of dynamics due to the flexibility of deep neural networks. Additionally, the probabilistic nature of the model class allows the uncertainty of the system to be modelled. In this work a deep SSM class and its parameter learning algorithm are explained in an effort to extend the toolbox of nonlinear identification methods with a deep learning based method. Six recent deep SSMs are evaluated in a first unified implementation on nonlinear system identification benchmarks.
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39.
  • Gerdin, Markus, et al. (författare)
  • Global Identifiability of Complex Models, Constructed from Simple Submodels
  • 2007
  • Ingår i: Modeling, Estimation and Control. - Linköping : Linköping University Electronic Press. - 9783540735694 ; , s. 123-133
  • Rapport (övrigt vetenskapligt/konstnärligt)abstract
    • It is a typical situation in modern modeling that a total model is built up from simpler submodels, or modules, for example residing in a model library. The total model could be quite complex, while the modules are well understood and analysed. A procedure to decide global parameter identifiability for such a collection of model equations of differential-algebraic nature is suggested. It is shown how to make use of the natural modularization of the model structure. Basically, global identifiability is obtained if and only if each module is identifiable, and the connecting signals can be retrieved from the external signals, without knowledge of the values of the parameters.
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40.
  • Gerdin, Markus, 1977-, et al. (författare)
  • On Parameter and State Estimation for Linear Differential-Algebraic Equations
  • 2007
  • Ingår i: Automatica. - Linköping : Elsevier. - 0005-1098 .- 1873-2836. ; 43:3, s. 416-425
  • Tidskriftsartikel (refereegranskat)abstract
    • The current demand for more complex models has initiated a shift away from state-space models towards models described by differential-algebraic equations (DAEs). These models arise as the natural product of object-oriented modeling languages, such as Modelica. However, the mathematics of DAEs is somewhat more involved than the standard state-space theory. The aim of this work is to present a well-posed description of a linear stochastic differential-algebraic equation and more importantly explain how well-posed estimation problems can be formed. We will consider both the system identification problem and the state estimation problem. Besides providing the necessary theory we will also explain how the procedures can be implemented by means of efficient numerical methods.
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