Results 251 to 260 of about 128,037 (313)

High-Precision and Efficient Calibration of Robot Polishing Systems Using an Adaptive Residual EKF Optimized by MIPO. [PDF]

Sensors (Basel)
Wang L, Yao Y, Ruan S, Li H, Zhang X, Zhang Y, Zang Z, Yu Z.   +7 more
europepmc   +1 more source

Cave reservoir characterization method driven by GA-KPCA and geological knowledge. [PDF]

PLoS One
Ren W, Chen H, Wang R, Zhang T, Li L.
europepmc   +1 more source

Kernel-DMD for multiome data integration and control. [PDF]

PLoS Comput Biol
Pierides I, Kramml HM, Waldherr S, Weckwerth W.   +3 more
europepmc   +1 more source

AI and Machine Learning for Proteomics-Driven Drug Discovery: Methods, Tools, and Best Practices. [PDF]

Curr Issues Mol Biol
Basak S.
europepmc   +1 more source

Hyperspectral-Imaging-Based ECNN-1D for Accurate Origin Classification of Fragrant Pears. [PDF]

Foods
Liang Z, Zhang X, Tan F, Di R, Zhang J, Xu W, Gao P, Zhang L.   +7 more
europepmc   +1 more source

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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
openaire   +4 more sources

Experimental Nonlinear Model Identification of a Highly Nonlinear Resonator

Journal of Vibration and Acoustics, 2018
In this work, two model identification methods are used to estimate the nonlinear large deformation behavior of a nonlinear resonator in the time and frequency domains. A doubly clamped beam with a slender geometry carrying a central intraspan mass when subject to a transverse excitation is used as the highly nonlinear resonator.
Yildirim, Tanju, Zhang, Jiawei, Sun, Shuaishuai, Alici, Gursel, Zhang, Shiwu, Li, Weihua   +5 more
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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.
István Vajk, Jenö Hetthéssy
openaire   +1 more source