Results 31 to 40 of about 17,988 (163)
IET Control Theory & ApplicationsThis article proposes an online solution to address the problem of closed‐loop system identification using multiple recursive least squares estimation protocols.
Amirreza Zaman, Wolfgang Birk
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Robust Recursive Estimation for Uncertain Systems With Delayed Measurements and Noises
IEEE Access, 2020 In this article, the problem of robust recursive estimation is studied for a class of uncertain systems with delayed measurements and delayed noises. The system model is subject to stochastic uncertainties which can be described by multiplicative noises.
Jianxin Feng +3 more
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Recursive prediction error methods for online estimation in nonlinear state-space models [PDF]
Modeling, Identification and Control, 1994 Several recursive algorithms for online, combined state and parameter estimation in nonlinear state-space models are discussed in this paper. Well-known algorithms such as the extended Kalman filter and alternative formulations of the recursive ...
Dag Ljungquist, Jens G. Balchen
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Identification of Wiener Systems with Recursive Gauss-Seidel Algorithm
Elektronika ir Elektrotechnika, 2023 The Recursive Gauss-Seidel (RGS) algorithm is presented that is implemented in a one-step Gauss-Seidel iteration for the identification of Wiener output error systems.
Metin Hatun
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Bayesian recursive estimation on the rotation group
2013 IEEE International Conference on Acoustics, Speech and Signal Processing, 2013 Tracking on the rotation group is a key component of many modern systems for estimation of the motion of rigid bodies. To address this problem, here we describe a Bayesian algorithm that relies on directional measurements for tracking on the special orthogonal (rotation) group.
Sofia Suvorova +2 more
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The Journal of Engineering, 2019 Modelling and simulation of clutter are important in radar signal processing, the G0 distribution is generally adopted to simulate the ground clutter in radar echoes. In order to improve the modelling accuracy of clutter modelling, the actual data should
Jiaxin Lu +3 more
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Optimal Nonlinear Prediction of Random Fields on Networks [PDF]
Discrete Mathematics & Theoretical Computer Science, 2003 It is increasingly common to encounter time-varying random fields on networks (metabolic networks, sensor arrays, distributed computing, etc.).This paper considers the problem of optimal, nonlinear prediction of these fields, showing from an information ...
Cosma Rohilla Shalizi
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IEEE Access, 2019 This paper investigates the robust output feedback model predictive control (ROFMPC) for the discrete-time linear system with norm-bound uncertainty and disturbance.
Jiandong Yang, Yuanli Cai, Baocang Ding
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On Asymptotically Efficient Recursive Estimation
The Annals of Statistics, 1978 Stochastic approximation procedures were shown by Sakrison to become asymptotically efficient estimators when used to minimize the Kullback-Leibler information, if certain conditions hold. Further results in this direction were obtained by Nevel'son and Has'minskij.
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Journal of Probability and Statistics, 2014 We propose an automatic selection of the bandwidth of the recursive kernel estimators of a probability density function defined by the stochastic approximation algorithm introduced by Mokkadem et al. (2009a).
Yousri Slaoui
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