Results 251 to 260 of about 519,710 (307)

A fast nonlinear model identification method

IEEE Transactions on Automatic Control, 2005
The identification of nonlinear dynamic systems using linear-in-the-parameters models is studied. A fast recursive algorithm (FRA) is proposed to select both the model structure and to estimate the model parameters. Unlike orthogonal least squares (OLS) method, FRA solves the least-squares problem recursively over the model order without requiring ...
Li, Kang, Peng, Jian Xun, Irwin, George
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Nonlinear Runoff Modeling: Parameter Identification

Journal of Hydraulic Engineering, 1983
A nonlinear functional rainfall‐runoff model is applied to an urban watershed (Curotte‐Papineau, Montreal) and the results are compared with those from the ILLUDAS model. Simulations are performed using a 5 minute time interval in order to better define the characteristics of the hydrographs.
Gilles G. Patry, Miguel A. Mariño
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Nonlinear modelling and identification

Proceedings of IEEE Systems Man and Cybernetics Conference - SMC, 2002
There has been a considerable increase in activity in the field of identification of nonlinear systems. Side by side with the identification of discrete-time models based on Kolmogorov-Gabor polynomials, artificial neural networks, etc., there has been a great deal of progress in the identification of continuous-time models governed by ordinary ...
A. Patra, H. Unbehauen
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Nonlinear Subspace Model Identification

IFAC Proceedings Volumes, 2004
Abstract Canonical variates state space (CVSS) modeling is a popular subspace linear model identification technique. A nonlinear extension of CVSS modeling approach was proposed (DeCicco and Cinar, 2000) . The modeling procedure consists of two steps: development of a multivariable nonlinear model for a set of latent variables and the linking of the ...
Ali Cinar, Jeffrey DeCicco
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Model quality in nonlinear sm identification

42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475), 2004
In the paper, the problem of identifying nonlinear regression models with "small" simulation errors is investigated. Models identified by classical methods minimizing the prediction error, do not necessary give "good" simulation error on future inputs and even boundedness of this error is not guaranteed.
MILANESE, Mario, NOVARA, Carlo
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Identification of nonlinear errors-in-variables models

Automatica, 2002
The publication deals with a generalization of a classical eigenvalue-decomposition method first developed for errors-in-variables linear system identification. An identification algorithm is presented for nonlinear, but linear in parameters errors-in-variables models using nonlinear polynomial eigenvalue-eigenvector decompositions.
Vajk, I., Hetthéssy, J.
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Nonlinear model identification for Artemia population motion

Nonlinear Dynamics, 2012
In this paper, two different nonlinear models for Artemia swarming are derived. In order to generate the data suitable for identification, a robot driving the Artemia population has been built. The obtained data have been then used to identify the parameters of a model based on Newton’s equations and a black-box NARX model implemented by neural ...
M. T. Rashid, FRASCA, MATTIA, A. A. Ali, R. S. Ali, FORTUNA, Luigi, M. G. Xibilia   +5 more
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Structure identification for nonlinear models

IFAC Proceedings Volumes, 2001
A block-oriented nonlinear system consists of a series of blocks. These blocks represent both memoryless nonlinearity and dynamic linear functional that comprise the overall input-output dynamics of the system. Under this category, the non linear systems are represented as Wiener, Hammerstein, Wiener-Hammerstein, and HammersteinWiener models, etc ...
Hsiao-Ping Huang, Ming-Wei Lee, Chun-Yun Tsai   +2 more
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