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Identification of Nonlinear Maps in Interconnected Systems
Proceedings of the 44th IEEE Conference on Decision and Control, 2006We offer a systematic algorithm for the identification of static nonlinear maps in interconnected systems. The class of systems considered are those consisting of linear time-invariant systems and static nonlinear functions. Under the conditions that the linear dynamics are known and the inputs to the nonlinearities are measurable, the identification ...
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Nonlinear system identification
Circuits, Systems, and Signal Processing, 2002This paper provides an overview of nonlinear system identification methodologies. The theory and application of nonlinear system identification is vast, and this overview is not intended to be comprehensive. Rather, the attempt here is to illustrate some of the salient features and key aspects of nonlinear system identification, especially those most ...
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The Identification Problem in Systems Nonlinear in the Variables
Econometrica, 1983This paper examines the identifiability of the coefficients of a single equation in a simultaneous equation model which is nonlinear only in the variables. The concept of identifiability in this model is motivated and developed using the closely related concept of observational equivalence.
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Nonlinear system identification: An overview
1993System identification consists in the characterization of a system from an analysis of observed input and output signals. In essence, the ultimate aim of system identification is prediction such that given a description of the system transfer parameters and the input, the output can be completely specified for any time.
Zoubir, AM, Boashash, B
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Identification of Nonlinear Systems
1989 American Control Conference, 1989It is extremely difficult to identify general nonlinear systems because of the number of unknowns involved. Moreover, since most design techniques assume a linear model, many of the nonlinearities that can be determined are essentially ignored. Why not develop nonlinear system identification techniques to reveal restricted classes of nonlinear systems ...
L.R. Hunt, R.D. DeGroat, D.A. Linebarger
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On the Identification of Nonlinear Systems
2000In many engineering disciplines the identification of dynamical systems from measured signals is an important task in the modelling process. If information on the structure of the system is available, the task is reduced to the identification of parameters. Often, however, either such information is not available or the system structure is known but is
K. Popp, J.-U. Bruns
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Nonlinear System Identification: An Overview of Common Approaches
2014Nonlinear mathematical models are essential tools in various engineering and scientific domains, where more and more data are recorded by electronic devices. How to build nonlinear mathematical models essentially based on experimental data is the topic of this entry.
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Identification of Nonlinear Systems
IFAC Proceedings Volumes, 1994Abstract A method is proposed for approximating dynamic nonlinear systems using parallel cascades of alternating dynamic linear and static nonlinear elements. A key advantage of the proposed method is its effectiveness in approximating nonlinear systems which cannot be well fit using the first few terms of a Volterra series.
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Nonlinear System Identification
2010This chapter contains sections titled: Historical Review Supervised Multilayer Networks Unsupervised Neural Networks: Kohonen Network Unsupervised Networks: Adaptive Resonance Theory Network Model Validation Summary References Recommended ...
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Identification of Nonlinear Systems
1982At first glance few problems arise in the area of structural dynamics which cannot be solved by means of today’s experimental and analytical tools. Thus, the elastodynamic characteristics can be determined by using common experimental or analytical methods if structural linearity can be assumed to be a proper approximation.
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