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A new approach for estimating the robustness of parameter estimates to measurement noise
2016
2016 American Control Conference (ACC)
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We establish an approximation of the covariance of a parameter estimate in this context, with several attractive theoretical properties. ...
Indeed, it agrees asymptotically with the Cramer-Rao based covariance estimate in the limit of increasing data, where the theoretical assumptions necessary for both methods hold. ...
Conclusion We have introduced a new method of estimating the covariance, with respect to Gaussian measurement noise, of a nominal parameter estimate in the grey-box system identification problem. ...
doi:10.1109/acc.2016.7525183
dblp:conf/amcc/RamanAP16
fatcat:2tuo3ad7qnei5ornmf4227r63u
Adaptive recursive M-robust system parameter identification using the QQ-plot approach
2011
IET Control Theory & Applications
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A new adaptive algorithm for the robust estimation of parameters of linear dynamic discrete-time systems in the presence of non-Gaussian impulsive noise within a measurement sequence is proposed in this ...
of measurement noise, demonstrates a high level of efficiency. ...
A new adaptive algorithm for the robust estimation of parameters of linear dynamic discrete-time systems in the presence of non-Gaussian impulsive noise within a measurement sequence is proposed in this ...
doi:10.1049/iet-cta.2009.0647
fatcat:ko4nzmhzsjcndc3g6kvr2vrlw4
Thrust acceleration estimation using an on-line non-linear recursive least squares algorithm
2008
Proceedings of the Institution of Mechanical Engineers. Part G, Journal of Aerospace Engineering
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The robustness of this new algorithm allows a significant increase of deviations in initial values of the estimated parameters. ...
In this article, a robust non-linear recursive algorithm, featuring a highly reduced computational load, is proposed to estimate the thrust acceleration of a typical flight vehicle. ...
RLS approach The RLS method calculates a new update for the Q2 parameter vectorx each time new data are received, and it requires time for the computation of each parameter. ...
doi:10.1243/09544100jaero371
fatcat:dlvppejs5zhhrgpk6qtmxwl6qy
Robust Adaptive Kalman Filter for estimation of UAV dynamics in the presence of sensor/actuator faults
2013
Aerospace Science and Technology
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For the presence of measurement faults, a Nonlinear Robust Adaptive EKF with the filter gain correction based on the evaluation of the posterior probability of the normal operation of system, given for ...
The developed Nonlinear Robust Adaptive EKF is applied for the parameter identification process of an EMA. ...
Acknowledgments This work was supported by TUBITAK (The Scientific and Technological Research Council of Turkey) under Grant 109M702. ...
doi:10.1016/j.ast.2012.12.003
fatcat:2au6xzzfm5byljnkrsdt4fbfxi
Robust measure transformed music for DOA estimation
2014
2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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The proposed approach is illustrated for direction-of-arrival (DOA) estimation in a simulation example that shows its advantages as compared to other robust MUSIC generalizations. ...
The proposed framework, called robust measure-transformed (MT) MUSIC, is based on applying a transform to the probability distribution of the received signals, i.e., transformation of the probability measure ...
Selection of the MT-function under the family of zero-centered Gaussian functions, parameterized by a scale parameter, results in a new algorithm called Gaussian MT-MUSIC. ...
doi:10.1109/icassp.2014.6854391
dblp:conf/icassp/TodrosH14
fatcat:md25fei5mvcl3abiwgtz2tdtrq
Adaptive Neural Networks For Robust Estimation Of Parameters Of Noisy Harmonic Signals
1996
Zenodo
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Publication in the conference proceedings of EUSIPCO, Trieste, Italy, 1996 ...
CONCLUSIONS Adaptive analogue neural networks represent a very promising approach for high-speed estimation of parameters of signals. ...
The purpose of this paper is to present novel on-line techniques for estimation of parameters of harmonics based on the least-squares (LS), total least-squares (TLS) and the robust TLS criteria. ...
doi:10.5281/zenodo.35989
fatcat:q26whh5kajeihdjchj7r7vt3hu
Robust adaptive estimators for nonlinear systems
2013
2013 Conference on Control and Fault-Tolerant Systems (SysTol)
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This paper is concerned with the development of new adaptive nonlinear estimators which incorporate adaptive estimation techniques for system noise statistics with the robust H technique. ...
The new filters are aimed at compensating the nonlinear dynamics as well as the system modeling errors by adaptively estimating the noise statistics and unknown parameters. ...
Although robust estimation approaches could handle uncertainties from modeling errors and system noises, the mean square error (MSE) of the output increases for H filter [2] . ...
doi:10.1109/systol.2013.6693823
fatcat:tokhtydztnbhlgw3rgrfkxzu3i
Robust radial basis function neural networks
1999
IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)
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This method based on using Support Vector Regression (SVR) approach as a robust procedure for determining the initial structure of RBF Neural Network. ...
In this paper, a novel method for robust nonlinear system identification is constructed to overcome the problems of traditional RBFNNs. ...
Acknowledgement The authors would like to thank the technical and financial supports provided by the National Iranian Gas Company-Sarkhoon & Qeshm Gas treating Company (NIGC-SQGC). ...
doi:10.1109/3477.809023
pmid:18252348
fatcat:fnpekr7ekzfnjbd7sc6lc62clq
Compressive sensing signal reconstruction by weighted median regression estimates
2010
2010 IEEE International Conference on Acoustics, Speech and Signal Processing
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We compare the performance of the proposed approach to those yielded by state-of-the-art CS reconstruction algorithms showing that our approach achieves a better performance for different noise distributions ...
In the first stage, an estimation of the sparse signal is found by recasting the reconstruction problem as a parameter location estimation for each entry in the sparse vector leading to the minimization ...
To mitigate the effect of impulsive noise in the compressive measurements, a more robust norm for the data-fitting term has to be used. ...
doi:10.1109/icassp.2010.5495738
dblp:conf/icassp/ParedesA10
fatcat:tfm4dhvxpzhq7lgvgtbxk5sb24
Robustness of SOC Estimation Algorithms for EV Lithium-Ion Batteries against Modeling Errors and Measurement Noise
2015
Mathematical Problems in Engineering
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This paper is a comparative study of robustness of SOC estimation algorithms against modeling errors and measurement noises. ...
State of charge (SOC) is one of the most important parameters in battery management system (BMS). ...
Conflict of Interests The authors declare that there is no conflict of interests regarding the publication of this paper. ...
doi:10.1155/2015/719490
fatcat:cmz64xrrirdbrmf755vkdgmtsu
Robust Position Estimation of an Autonomous Mobile Robot
[chapter]
2008
Frontiers in Robotics, Automation and Control
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is to propose a new approach to improve existing data fusion and filtering techniques for robust localization of a mobile robot. ...
Conclusion This research work introduces a multiple model approach for the robust localization of a mobile robot. ...
The book covers topics such us modeling and practical realization of robotic control for different applications, researching of the problems of stability and robustness, automation in algorithm and program ...
doi:10.5772/6323
fatcat:qulbgmfrsvdybamaw4nppdglyy
Robust Processing of Nonstationary Signals
2010
EURASIP Journal on Advances in Signal Processing
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The main tool is the robust DFT that can be used for development of various robust tools in the spectral domain. The paper "An overview of the adaptive robust DFT" (A. ...
The proposed approach combines the robust DFT evaluation in order to get filtered signal with removed and/or reduced influence of the impulsive noise and the time-frequency representations with the complex ...
A new gradient fidelity term is designed to force the gradients of desired image to be close to the curvelet approximation gradients. ...
doi:10.1155/2010/724746
fatcat:szdryrbksja2feukzjadkrnkgy
The outlier process: unifying line processes and robust statistics
1994
Proceedings of IEEE Conference on Computer Vision and Pattern Recognition CVPR-94
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This outlier-processes approach provides a general framework which subsumes the traditional lane-process approaches as well as a wade class of robust estimation problems. ...
We also characterize a class of robust statistical problems for which an equivalent outlier-process formulation exists and give a straightforward method for converting a robust estimation problem into ...
Gindi A. Jepson, and E. Mjolsness for their helpful comments. ...
doi:10.1109/cvpr.1994.323805
dblp:conf/cvpr/BlackR94
fatcat:6lhpoxontjfl3jmialbaaetmxy
Objective Estimation of Sensory Thresholds Based on Neurophysiological Parameters
2019
Frontiers in Neuroscience
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However, there exists no assumption-independent gold standard for the estimation of thresholds based on neurophysiological parameters, although a reliable estimation method is crucial for both scientific ...
Whenever the threshold is estimated based on such measures, the standard approach until now is the subjective setting-either by eye or by statistical means-of the threshold to the value where at least ...
SUPPLEMENTARY MATERIAL The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fnins. 2019.00481/full#supplementary-material ...
doi:10.3389/fnins.2019.00481
pmid:31156368
pmcid:PMC6532536
fatcat:rzlv6evwwnfuhjgcwcg2ehfwti
A New Choice of Penalty Function for Robust Multiuser Detection Based on$M$-Estimation
2005
IEEE Transactions on Communications
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In this letter, we propose a new robust MUD, called detector, for non-Gaussian noise. We consider the Gaussianmixture model for non-Gaussian or impulsive noise. ...
The proposed method uses a parametric cost function, where the parameter is selected using the difference between the asymptotic variance of estimation error of the detector and that of the minimax detector ...
We define a distance measure as (13) where the limits and are selected so as to span the range of variation of the noise-model parameters. ...
doi:10.1109/tcomm.2004.842001
fatcat:ugvxeduvdnbpnhpgnvagzwgg6q
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