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Neurocomputing (Amsterdam), ISSN 0925-2312, 2019, Volume 329, pp. 424 - 432
Kernel adaptive filters (KAFs) with growing network structures incur high computational burden. Generally, sparsification methods are introduced to curb the... 
Kernel adaptive filters | Nyström method | Learning | Kernel recursive maximum correntropy | Nystrom method | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Journal Article
IEEE transactions on instrumentation and measurement, ISSN 0018-9456, 6/2020, pp. 1 - 1
The unscented Kalman filter (UKF) provides a powerful tool for power system forecasting-aided state estimation (FASE). However, when the power systems are... 
Power system dynamics | non-Gaussian disturbances | minimum error entropy | Forecasting-aided state estimation | Entropy | Kalman filters | Noise measurement | State estimation | Covariance matrices | unscented Kalman filter
Journal Article
IEEE transactions on circuits and systems. I, Regular papers, ISSN 1558-0806, 2018, Volume 65, Issue 10, pp. 3390 - 3403
Journal Article
IEEE Transactions on Circuits and Systems II: Express Briefs, ISSN 1549-7747, 11/2018, Volume 65, Issue 11, pp. 1788 - 1792
Journal Article
IEEE transactions on circuits and systems. I, Regular papers, ISSN 1558-0806, 2019, Volume 66, Issue 11, pp. 4265 - 4277
The Hilbert space embedding provides a powerful and flexible tool for dealing with the nonlinearity and high-order statistics of random variables in a... 
maximum correntropy criterion | Estimation | conditional embedding operator | Predictive models | Cost function | Random variables | Kalman filters | Noise measurement | kernel Kalman-type filter | Nyström approximation | Kernel | Hilbert space embedding | Nystrom approximation | ENGINEERING, ELECTRICAL & ELECTRONIC | TIME-SERIES
Journal Article
IEEE access, ISSN 2169-3536, 2018, Volume 6, pp. 10540 - 10552
This paper presents novel kernel adaptive filters with feedback, namely, kernel recursive maximum correntropy with multiple feedback (KRMC-MF) and its... 
Kernel adaptive filters | feedback structure | Signal processing algorithms | minimum mean square error | Mean square error methods | Cost function | Robustness | maximum correntropy | Kernel | Periodic structures | Convergence | convergence
Journal Article
2016 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI), 10/2016, pp. 925 - 929
Cauchy estimator has been successfully applied to the statistical learning owing to its unique distribution characteristics and robustness to outliers. In this... 
Computational modeling | Signal processing algorithms | Cost function | Robustness | Steady-state | Kernel | Convergence
Conference Proceeding
2018 Tenth International Conference on Advanced Computational Intelligence (ICACI), 03/2018, pp. 140 - 144
This paper presents a novel kernel least square algorithm with mixed kernel (KLMS-MK) to improve the filtering performance of kernel least mean square (KLMS).... 
Gaussian kernel | mixed parameter | Gaussian noise | Time series analysis | Signal processing algorithms | Approximation algorithms | Kernel least mean square algorithm | Kernel | Laplace kernel | Testing | Convergence | Mixed parameter
Conference Proceeding
2017 20th International Conference on Information Fusion (Fusion), 07/2017, pp. 1 - 7
In this paper, the maximum correntropy (MC) criterion is used as the cost function in the online sequential extreme learning machine (OS-ELM) algorithm and... 
Gaussian noise | Time series analysis | Training data | Cost function | Feedforward neural networks | Kernel | Joining processes
Conference Proceeding
2017 20th International Conference on Information Fusion (Fusion), 07/2017, pp. 1 - 7
This paper presents a novel nonlinear adaptive filter method, namely, Hammerstein adaptive filter with single feedback under minimum mean square error... 
Training | Algorithm design and analysis | Adaptive filters | Estimation | Mean square error methods | Convergence | Periodic structures
Conference Proceeding
04/2019
To date most linear and nonlinear Kalman filters (KFs) have been developed under the Gaussian assumption and the well-known minimum mean square error (MMSE)... 
Journal Article
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