Results 281 to 290 of about 2,620,504 (318)
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On the Identification of Nonlinear Systems
IFAC Proceedings Volumes, 1982Abstract For the identification of systems in which the nonlinear element is in the feedback path, a new technique based on the Volterra characterisation of nonlinear system, is presented. The method is shown to have distinct computational advantages. Simulation studies using the proposed method are given.
N.C. Jagan, D.C. Reddy
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Identification in fuzzy systems
IEEE Transactions on Systems, Man, and Cybernetics, 1984Given are fuzzy relational equations of the type \(Y=X\circ R\), \(Y=X*R\), \(Y=X\square R\), where X,Y denote fuzzy sets of input and output, R a fuzzy relation, and \(\circ\), *, \(\square\) are sup-min, sup-prod, inf-max composition operators, respectively. This paper deals with identification methods in fuzzy systems.
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An invariance in system identification
IEEE Transactions on Acoustics, Speech, and Signal Processing, 1987In simulations and analysis involving adaptive system identification with FIR filters, a white noise input spectrum is usually assumed. We consider in this correspondence the effect of an autoregressive (all-pole) input. In particular, we prove that all but P of the optimum tap weights are invariant to the pole locations, where P is the number of poles
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Outliers in system identification
2017 IEEE 56th Annual Conference on Decision and Control (CDC), 2017This paper is dedicated to Dr. Roberto Temple. The topic, outliers in system identification, was initially started with a discussion with Roberto in the early 2000. The first part of the paper summaries the approach, optimization with few violated constrains for linear bounded error parameter estimation, that was appeared in IEEE Trans.
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System identification in a real world
2014 IEEE 13th International Workshop on Advanced Motion Control (AMC), 2014In this paper we discuss how to identify a mathematical model for a (non)linear dynamic system starting from experimental data. In the initial step, the frequency response function is measured, together with the properties of the disturbing noise and the nonlinear distortions.
Johan Schoukens +8 more
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International Journal of Quantum Information, 2005
The joint measurement approach has been shown to detect more information in quantum system. In this paper, we propose a quantum identification algorithm based on the joint quantum measurement. Through this, we can collectively compare an unknown quantum composite system with those in the database.
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The joint measurement approach has been shown to detect more information in quantum system. In this paper, we propose a quantum identification algorithm based on the joint quantum measurement. Through this, we can collectively compare an unknown quantum composite system with those in the database.
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Identification of partially-known systems
Automatica, 1992zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Peter J. Gawthrop +2 more
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Anaerobic Identification Systems
Clinics in Laboratory Medicine, 1985Commercially produced prepackaged "kit" microsystems were evaluated for the identification of anaerobes. The API 20A and Minitek Anaerobe II systems by themselves were inadequate; even with the use of supplemental tests, agreement of identifications with a conventional method was only fair.
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Morphogenetic approach to system identification
International Journal of Intelligent Systems, 2009Summary: We propose a novel approach to system identification based on Morphogenetic Theory (MT). Given a context \(H\) defined by a set of \(M\) objects, each described by a set of \(N\) attributes, and a vector \(X\) of desired outputs for each object, MT combines notions from formal concept analysis and tensor calculus so as to generate a ...
MARCELLONI, FRANCESCO +2 more
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Iterative Identification of Hammerstein Systems
Automatica, 2007zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Yun Liu 0019, Er-Wei Bai
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