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Keywords
(8)
Bilinear System
Nonlinear Model
Nonlinear System
Parameter Estimation
Recursive Least Square
Singular Value Decomposition
System Identification
White Noise
Related Publications
(16)
Decoupling the linear and nonlinear parts in Hammerstein model identification
Recursive identification of Hammerstein systems with discontinuous nonlinearities containing deadzones
Identification of blockoriented nonlinear systems using orthonormal bases
An iterative method for the identification of nonlinear systems using a Hammerstein model
A noniterative method for identification using Hammerstein model
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An optimal twostage identification algorithm for Hammerstein–Wiener nonlinear systems * * This paper was not presented at any IFAC meeting. This paper was recommended for publication in revised form by editor Associate Editor B. Ninness under the direction of Editor Torsten Söderström
An optimal twostage identification algorithm for Hammerstein–Wiener nonlinear systems * * This paper was not presented at any IFAC meeting. This pape
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An optimal twostage identification algorithm for Hammerstein–Wiener nonlinear systems * * This paper was not presented at any IFAC meeting. This paper was recommended for publication in revised form by editor Associate Editor B. Ninness under the direction of Editor Torsten Söderström
(
Citations: 69
)
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ErWei Bai
An optimal twostage identification algorithm is presented for Hammerstein–Wiener systems where two static nonlinear elements surround a linear block. The proposed algorithm consists of two steps: The first one is the recursive least squares and the second one is the
singular value decomposition
of two matrices whose dimensions are fixed and do not increase as the number of the data point increases. Moreover, the algorithm is shown to be convergent in the absence of noise and convergent with probability one in the presence of white noise.
Journal:
Automatica
, vol. 34, no. 3, pp. 333338, 1998
DOI:
10.1016/S00051098(97)001982
Cumulative
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www.sciencedirect.com
)
Citation Context
(25)
...The stochastic method [4] is employed in preference to the over parameterization method [
8
]...
Steven W. Su
,
et al.
Modelling and Control for Heart Rate Regulation during Treadmill Exerc...
...Narendra & Gallman, 1966; Hunter & Korenberg, 1986; Juusola et al., 1995;
Bai, 1998;
Westwick & Kearney, 2001)...
...Taking the single leading SVD term produces an approximation to the fullrank model, C�i ≈ w�bi, giving a bilinear input nonlinearity model (
Bai, 1998
)...
Misha B. Ahrens
,
et al.
Inferring input nonlinearities in neural encoding models
...In the identification area of nonlinear systems, there exists a large amount of research exploring different approaches; see, e.g., [
3
, 4, 5, 6, 35, 36, 37]...
...For Hammerstein–Wiener nonlinear models, Bai reported a twostage identification algorithm based on the recursive least squares and the singular value decomposition [
3
] and a blind identification approach [5]...
...There are several ways to normalize the gains [
3
, 8, 22]...
...Of course, the singular value decomposition technique or least squares optimization methods can also be used to find the estimate of c [
3
, 7]...
Feng Ding
,
et al.
Adaptive Digital Control of Hammerstein Nonlinear Systems with Limited...
...whiteness) and the nonlinearity under consideration [2] or by using a process known as overparameterization [4,
1
]...
...Although this approach may seem adhoc at flrst, it is essentially an application of Bai’s overparameterization approach [
1
] to LSSVMs...
...Again, this is the equivalent of the SVDstep that is generally encountered in overparameterization methods [4,
1
]...
...As was mentioned in subsection 4.1, the presented technique is closely related to the overparameterization approach [4,
1
]...
Ivan Goethals
,
et al.
Identification of MIMO Hammerstein models using least squares support ...
...A similar methodology was employed in [
1
] for a scalar Hammerstein–Wiener model...
Juan C. Gomez
,
et al.
Subspace Identification of Multivariable Hammerstein and Wiener Models
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Journal:
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A noniterative method for identification using Hammerstein model
(
Citations: 112
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Journal:
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Consistency of the leastsquares identification method
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Journal:
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An iterative method for the identification of nonlinear systems using a Hammerstein model
(
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K. Narendra
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Journal:
IEEE Transactions on Automatic Control  IEEE TRANS AUTOMAT CONTR
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On the convergence of an iterative algorithm used for Hammerstein system identification
(
Citations: 87
)
P. Stoica
Journal:
IEEE Transactions on Automatic Control  IEEE TRANS AUTOMAT CONTR
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Citations
(69)
Identification of Hammerstein Systems with Quantized Observations
(
Citations: 3
)
Yanlong Zhao
,
JiFeng Zhang
,
Le Yi Wang
,
Gang George Yin
Journal:
Siam Journal on Control and Optimization  SIAM J CONTR OPTIMIZAT
, vol. 48, no. 7, pp. 43524376, 2010
Bayesian method for multirate data synthesis and model calibration
(
Citations: 1
)
Xinguang Shao
,
Biao Huang
,
Jong Min Lee
,
Fangwei Xu
,
Aris Espejo
Journal:
Aiche Journal  AICHE J
, 2010
Identification of HammersteinWiener Models Based on Bias Compensation Recursive Least Squares
Yan LI
,
ZhiZhong MAO
,
Yan WANG
,
Ping YUAN
,
MingXing JIA
Journal:
Acta Automatica Sinica
, vol. 36, no. 1, pp. 163168, 2010
A Novel Predistorter Design for Nonlinear Power Amplifier with Memory Effects in OFDM Communication Systems Using Orthogonal Polynomials
Yitao Zhang
,
Kiyomichi Araki
Journal:
Ieice Transactions  IEICE
, vol. 93C, no. 7, pp. 983990, 2010
Identification of Hammerstein systems without explicit parameterisation of nonlinearity
(
Citations: 5
)
Jiandong Wang
,
Akira Sano
,
Tongwen Chen
,
Biao Huang
Journal:
International Journal of Control  INT J CONTR
, vol. 82, no. 5, pp. 937952, 2009