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Adaptive filters with individual adaptation of parameters
IEEE Transactions on Circuits and Systems, 1986Conventional gradient-type adaptive filters use the fixed convergence factor \mu which is normally chosen to be the same for all the filter parameters. In this paper, we propose to use individual convergence factors which are optimally tailored to adapt individual filter parameters.
W. Mikhael +4 more
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Optimal adaptive estimation: Structure and parameter adaptation
1970 IEEE Symposium on Adaptive Processes (9th) Decision and Control, 1970Optimal structure and parameter adaptive estimators have been obtained for continuous as well as discrete data gaussian process models with linear dynamics. Specifically, the essentially nonlinear adaptive estimators are shown to be decomposable (partition theorem) into two parts, a linear non-adaptive part consisting of a bank of Kalman-Bucy filters ...
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A parameter adaptive DE algorithm on real-parameter optimization
Journal of Intelligent & Fuzzy Systems, 2020Differential Evolution (DE) algorithm generates a population of individuals by encoding with a floating point vector, and it is a simple and effective population-based stochastic optimization algorithm for global optimization of continuous space.
Jeng-Shyang Pan 0001 +4 more
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2012 International Conference on Industrial Control and Electronics Engineering, 2012
This paper investigates the problem of parameters estimation and adaptive synchronization of chaotic systems with adaptive parameters perturbation. Based on Lyapunov stability theory, the general expression of the suitable adaptive synchronization controller is developed.
WeiXun Gao, Yuanjie Li, Yuhua Xu
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This paper investigates the problem of parameters estimation and adaptive synchronization of chaotic systems with adaptive parameters perturbation. Based on Lyapunov stability theory, the general expression of the suitable adaptive synchronization controller is developed.
WeiXun Gao, Yuanjie Li, Yuhua Xu
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Adaptive tuning of SLIC parameter K
Multimedia Tools and Applications, 2021The well-known simple linear iterative clustering (SLIC) is the most effective among the existing algorithms for superpixel segmentation, which requires manual tuning of the number of superpixels K. The optimal value of the parameter K of the SLIC algorithm for a given image is yet an open issue.
Shakir Ullah, Naeem Bhatti, Muhammad Zia
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1996
Control over parameter passing is a key issue in distributed object-oriented applications. The two simplest solutions — passing objects by global reference and passing objects by deep copy — both have significant drawbacks. Instead, an intermediate amount of copying is often best.
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Control over parameter passing is a key issue in distributed object-oriented applications. The two simplest solutions — passing objects by global reference and passing objects by deep copy — both have significant drawbacks. Instead, an intermediate amount of copying is often best.
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Adaptive charts with variable parameters
Computational Statistics & Data Analysis, 2011zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Adaptive parameter identification
IEEE Transactions on Automatic Control, 1972An extended Kalman filter with a fictitious noise input is developed for tracking time-varying parameters. An adaptation algorithm is used for adjusting the covariance of the fictitious noise according to the magnitude of the measured residuals and applied to the tracking of time-varying VTOL parameters.
H. Kaufman, D. Beaulier
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Parameter adaptive control algorithms—A tutorial
Automatica, 1980An introduction is given to adaptive (self-tuning) control algorithms with recursive parameter estimation, which have obtained increasing attention in recent years. These algorithms result from combinations of recursive parameter estimation algorithms and easy to design control algorithms.
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Gaussian adaptation based parameter adaptation for differential evolution
2014 IEEE Congress on Evolutionary Computation (CEC), 2014Differential Evolution (DE), a global optimization algorithm based on the concepts of Darwinian evolution, is popular for its simplicity and effectiveness in solving numerous real-world optimization problems in real-valued spaces. The effectiveness of DE is due to the differential mutation operator that allows DE to automatically adjust between the ...
Rammohan Mallipeddi +3 more
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