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Identification of a Time-Varying Parameter of a Noiseless Sinusoidal Signal
Automation and Remote Control, 2022This paper considers the problem of identifying an unknown time-varying parameter \(\omega(t)\) of a noiseless sinusoidal signal of the form \[ y(t) = \alpha(t) \sin(\omega(t) + \varphi), \] where \(y(t)\) is a directly measurable signal, \(\alpha(t)\) is an unknown amplitude, \(\omega(t)\) is an unknown time-varying parameter, and \(\varphi\) is an ...
Alexey A. Bobtsov +3 more
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A VSS identification scheme for time-varying parameters
Automatica, 2003A single input single output nonlinear control system is considered in the presence of an unknown (but bounded) time-varying parameter. An instantaneous VSS identification scheme is proposed under suitable assumptions. This scheme is based on the observation that the system (originally rational in the parameter) becomes linear in the parameter once ...
Jian-Xin Xu 0001 +2 more
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Quantile Search with Time-Varying Search Parameter
2018 52nd Asilomar Conference on Signals, Systems, and Computers, 2018We consider the problem of active learning in the context of spatial sampling, where the sampling cost is a function of both the number of samples taken and the distance traveled during the sampling procedure. We present Uniform-to-Binary (UTB) search, a novel algorithm in this setting.
John Lipor, Gautam Dasarathy
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Bounded-error tracking of time-varying parameters
IEEE Transactions on Automatic Control, 1994Bounded-error estimation aims at characterizing the set of all parameter vectors consistent with given data and prior bounds on acceptable values for the errors. In this paper, two recursive polyhedric description algorithms are presented for tracking time-varying parameters of models with outputs linear in their parameters. The performances of the two
Hélène Piet-Lahanier, Eric Walter
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Estimation for Time-Varying Parameters
1991Tracking or estimating a system or a signal whose properties vary with time is a fundamental problem in system identification as well as in signal processing. The basic time-varying model is that of a regression: $$ {y_k} = \varphi _k^\tau {\theta _k} + vk,{\text{ }}\forall k \geqslant 0 $$ (10.1) where yk and v k are the scalar output and ...
Chen Han-Fu, Lei Guo
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An adaptive filter for time‐varying‐parameter models
International Journal of Adaptive Control and Signal Processing, 1990AbstractA non‐linear adaptive filter is introduced and applied to the classical problem of estimating time‐varying‐parameter linear regression models with unknown error variances and a time‐varying transition matrix. The filter is basically a new result in what is known as Sridhar filtering theory.
Abutaleb, A., Papaionnou, M.
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On the Identification of Hammerstein Systems with Time-Varying Parameters
2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2007A growing emphasis on the analysis of time-varying systems has intensified the need for simpler and more efficient identification methods for these systems. In this contribution, we examine the time-varying Hammerstein structure, comprising a memoryless nonlinearity with time-varying parameters followed by a time-varying linear filter.
Bashiru I, Ikharia, David T, Westwick
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IDENTIFICATION OF TIME VARYING PARAMETERS OF THE ROBOT DYNAMICS
IFAC Proceedings Volumes, 1988Abstract The robot dynamics consists of the dynamics of the mechanics, the servo-drives, and the robot controller structure. The dynamics of the mechanics is simulated by the equation of motion which is set up automatically by a computer program. The robot controller is taken into account too, to simulate the robot dynamics.
U. Zimmermann +3 more
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LMS-LIKE ESTIMATION FOR TIME VARYING PARAMETERS
Acta Mathematica Scientia, 1991The authors consider linear models of the type \(y_ n=\varphi^ \tau_ n\theta_ n+v_ n\), \(n\geq 0\), where \(\theta_ n\) denotes a (possibly random) time-dependent parameter of interest, \(y_ n\) the (real-valued) system output, \(\varphi_ n\) an \(r\)-dimensional regressor, and \(v_ n\) the system noise.
Chen, H. F., Guo, L., Zhang, J. F.
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Parameter estimation on linear time-varying systems
Journal of the Franklin Institute, 2011zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Luiz Cláudio Andrade Souza +1 more
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