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从阴极引脚接点互换和偏转线圈引线互换两个方面对“引脚线互换法”及其用法进行了阐述。该法可巧妙地诊断彩电或彩显偏(缺)色故障和非对称性异常光栅故障。 相似文献
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Lei Sun Kar-Ann Toh Badong Chen Zhiping Lin 《Journal of The Franklin Institute》2018,355(4):2022-2040
In binary pattern classification, the reliabilities of statistics obtained from the samples of the two categories are generally different. When the statistics are used for modeling a classifier, such reliability difference could impact the generalization performance. We formulate a disparity index to show the statistical disparity based on the generalized eigenvalue decomposition of the categorical moment matrices. It is shown that this disparity index can effectively indicate the reliability difference between the two categories. The obtained reliability difference is subsequently utilized to adjust the regularization term of a classifier for effective learning generalization. Our experiments based on 10 real-world benchmark data sets validate the effectiveness of the proposed method. 相似文献
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阐述了如何使用“ZDSoft．net教育统计系统”规范中小学教育装备统计管理，介绍了其使用及操作的几点关键性的经验和技巧。 相似文献
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This paper investigates the robustness, uniqueness, sufficient condition and the necessary condition for the minimum error entropy (MEE) estimation. For the robustness aspect, we show that the MEE estimator for a Gaussian nominal model is robust with respect to a relative entropy mismodeling criterion as well as the minimum mean-square error (MMSE) estimations. For the uniqueness aspect, we demonstrate by means of examples that for the singular case, the optimum solution of the MEE estimation will be nonunique. For the sufficient and the necessary condition, the former is established by the independence condition, and the later by score orthogonality condition. A specific example illustrates that the score orthogonality condition is just a necessary condition and not a sufficient one, because if an estimator satisfies the score orthogonality condition, it may be a local minimum or even a local maximum of the error entropy in a certain direction. 相似文献
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Wentao Ma Xinyu Qiu Jiandong Duan Yingsong Li Badong Chen 《Journal of The Franklin Institute》2018,355(4):1596-1613
This work studies the problem of kernel adaptive filtering (KAF) for nonlinear signal processing under non-Gaussian noise environments. A new KAF algorithm, called kernel recursive generalized mixed norm (KRGMN), is derived by minimizing the generalized mixed norm (GMN) cost instead of the well-known mean square error (MSE). A single error norm such as lp error norm can be used as a cost function in KAF to deal with non-Gaussian noises but it may exhibit slow convergence speed and poor misadjustments in some situations. To improve the convergence performance, the GMN cost is formed as a convex mixture of lp and lq norms to increase the convergence rate and substantially reduce the steady-state errors. The proposed KRGMN algorithm can solve efficiently the problems such as nonlinear channel equalization and system identification in non-Gaussian noises. Simulation results confirm the desirable performance of the new algorithm. 相似文献
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从激发兴趣、丰富想象、启发思维、培养品质等几个方面阐述了实验操作与实践活动在数学教学中的作用。 相似文献
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Jiuwen Cao Tianlei Wang Luming Shang Xiaoping Lai Chi-Man Vong Badong Chen 《Journal of The Franklin Institute》2018,355(4):1539-1558
Earth surface vibrations generated by passing vehicles, excavation equipment, footsteps, etc., attract increasing attentions in the research community due to their wide applications. In this paper, we investigate the periodic vibration source localization problem, which has recently shown significance in excavation device detection and localization for urban underground pipeline network protection. An intelligent propagation distance estimation algorithm based on a novel fundamental frequency energy distribution (FBED) feature is developed for periodic vibration signal localization. Contributions of the paper lie in three aspects: 1) a novel frequency band energy distribution (FBED) feature is developed to characterize the property of vibrations at different propagation distances; 2) an intelligent propagation distance estimation model built on the FBED feature with machine learning algorithms is proposed, where for comparisons, the support vector machine (SVM) for regression and regularized extreme learning machine (RELM) are used; 3) a localization algorithm based on the distance-of-arrival (DisOA) estimation using three piezoelectric transducer sensors is given for source position estimation. To testify the effectiveness of the proposed algorithms, case studies on real collected periodic vibration signals generated by two electric hammers with different fundamental frequencies are presented in the paper. The transmission medium is the cement road and experiments on vibration signals recorded at different propagation distances are conducted. 相似文献
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