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Keywords = fast kernel entropy optimization

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17 pages, 800 KB  
Article
A Novel Adaptive State Detector-Based Post-Filtering Active Control Algorithm for Gaussian Noise Environment with Impulsive Interference
by Wenzhao Zhu, Shengguo Shi, Lei Luo and Jinwei Sun
Appl. Sci. 2019, 9(6), 1176; https://doi.org/10.3390/app9061176 - 20 Mar 2019
Cited by 6 | Viewed by 3085
Abstract
For Gaussian noise with random or periodic impulsive interference, the conventional active noise control (ANC) methods with finite second-order moments may fail to converge. Furthermore, the intensity of impulsive noise typically varies over time in the actual application, which also decreases the performance [...] Read more.
For Gaussian noise with random or periodic impulsive interference, the conventional active noise control (ANC) methods with finite second-order moments may fail to converge. Furthermore, the intensity of impulsive noise typically varies over time in the actual application, which also decreases the performance of conventional active impulsive noise control methods. To address these problems, a novel adaptive state detector based post-filtering active control algorithm is proposed. In this work, information entropy with adaptive kernel size is first introduced into the cost function of a post-filtering algorithm to improve its tracking. To enhance the robust performance of adaptive filters when impulsive interference happens, a recursive optimal threshold selecting method is also developed and analyzed by statistical theories. Simulations show that the new method has fast tracking ability in non-impulsive noise environment and keeps robust when impulsive interference happens. It also works well for the impulsive noise of different degrees. Experiment results confirm the effectiveness of the proposed algorithm. Full article
(This article belongs to the Special Issue Active and Passive Noise Control)
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15 pages, 2283 KB  
Article
Harmonic Source Localization Approach Based on Fast Kernel Entropy Optimization ICA and Minimum Conditional Entropy
by Tianlei Zang, Zhengyou He, Ling Fu, Jing Chen and Qingquan Qian
Entropy 2016, 18(6), 214; https://doi.org/10.3390/e18060214 - 1 Jun 2016
Cited by 10 | Viewed by 5992
Abstract
Based on the fast kernel entropy optimization independent component analysis and the minimum conditional entropy, this paper proposes a harmonic source localization method which aims at accurately estimating harmonic currents and identifying harmonic sources. The injected harmonic currents are estimated by the fast [...] Read more.
Based on the fast kernel entropy optimization independent component analysis and the minimum conditional entropy, this paper proposes a harmonic source localization method which aims at accurately estimating harmonic currents and identifying harmonic sources. The injected harmonic currents are estimated by the fast kernel entropy optimization independent component analysis (FKEO-ICA) in the absence of prior knowledge of harmonic impedances. Then, the minimum conditional entropy is applied to locate the harmonic sources based on the estimated harmonic currents. The proposed harmonic source localization method is validated on the IEEE 34-bus system. By applying the correlation coefficient and three error evaluation indicators, comparison has been made among the performances of the FKEO-ICA and three other ICA algorithms. The results show that the FKEO-ICA algorithm could achieve a significantly better accuracy of harmonic current estimation, while the minimum conditional entropy could determine the locations of harmonic sources precisely. Full article
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