Journal Article10.3182/20110828-6-IT-1002.03212
A Fast Approximation Algorithm for Set-Membership System Identification
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TL;DR: The nearest point approximation to the exact Set Membership model, found in literature, is analyzed and a novel approximation is proposed, whose complexity does not depend on the size of the data set.
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About: This article is published in IFAC Proceedings Volumes. The article was published on 01 Jan 2011. The article focuses on the topics: Set function & Approximation algorithm.
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Citations
Parameters Identification and Gas Behavior Characterization of DBD Systems
TL;DR: In this paper, the authors proposed an identification method for dielectric barrier discharge (DBD) systems, based on input-output (current-voltage) experimental measurements, where the DBD is modeled using an equivalent electric circuit associated with a differential equation that describes the dynamics of its conductance.
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3D Model Identification of a Soft Robotic Neck
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TL;DR: In this paper, the authors explore different state-of-the-art identification methods for the soft neck, in order to find a reliable plant model, considering the planar deflection of the link as a starting point for future analysis.
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Set membership identification of an excimer lamp for fast simulation
TL;DR: Black-box models of the electrical behavior and UV radiation process of an excimer lamp are estimated, employing Set Membership techniques, and it is found that the obtained models allow faster simulations than the original Set Membership algorithm while maintaining good prediction capabilities, making them useful in power sources design.
3
Set Membership methods in identification, prediction and filtering of nonlinear systems (semi-plenary lecture)
Mario Milanese,Carlo Novara +1 more
- 01 Jan 2009
TL;DR: Some of the main results developed by the authors are presented, i.e. an optimal identification algorithm, two almost-optimal prediction algorithms and an almost-Optimal filtering algorithm are presented within the presented unified SM inference making problem.
2
References
Neural networks for system identification
TL;DR: Two approaches are presented for utilization of neural networks in identification of dynamical systems using a Hopfield network and a set of orthogonal basis functions and Fourier analysis to construct a dynamic system in terms of its Fourier coefficients.
304
Neural Networks for System Identification
Reynold Chu,Rahmat A. Shoureshi,M.F. Tenorio +2 more
- 21 Jun 1989
TL;DR: Two approaches are presented for utilization of neural networks in identification of dynamical systems using a Hopfield network and a set of orthogonal basis functions and Fourier analysis to construct a dynamic system in terms of its Fourier coefficients.
130
Kernel based partially linear models and nonlinear identification
TL;DR: This note proposes partially linear models with least squares support vector machines (LS-SVMs) for nonlinear ARX models and illustrates how full black-box models can be improved when prior information about model structure is available.
108
Set membership identification of nonlinear systems
Carlo Novara,Mario Milanese +1 more
- 12 Dec 2000
TL;DR: This work investigates the problem of finding upper and lower bounds of a real valued function of several variables, on the base of a set of noise corrupted values of the function evaluated at a given set of variables and on some assumptions on function regularity and on noise bounds.
Predictive model of a DBD lamp for power supply design and method for the automatic identification of its parameters
TL;DR: In this paper, an electrical model for a dielectric barrier discharge (DBD) is proposed, with the aim of its application in power supply design process, and an identification method, which finds the actual value of the parameters in a model, is presented.