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Informationization and globalization provide a brand new development opportunity to China. As a developing country whose industrialization hasn't completed and way to realizing informationization is extremely rough, propelling the integration of informationization and Rail Transportation Equipment Industry is China's inevitable choice to release various development vitality and build a powerful socialist...
In this paper, we study the performance of mean square error (MSE) and Gaussian entropy criteria for linear and widely linear complex filtering. The MSE criterion cannot exploit the full second-order statistics of the error signal. To this end, we propose a new Gaussian entropy criterion to exploit the full second-order statistics of the error signal, and compare the performance of the two criteria...
Independent component analysis (ICA) has proven useful for the analysis of functional magnetic resonance imaging (fMRI) data. In this paper, we compare the performance of three ICA algorithms and show the importance of taking sample correlation information into account. The three ICA algorithms are Infomax, the most widely used algorithm for fMRI analysis, entropy bound minimization (EBM) that adapts...
We propose a new entropy rate estimator for a second and/or higher-order correlated source by modeling it as the output of a linear filter, which can be mixed-phase, driven by Gaussian or non-Gaussian noise. Based on this estimator, we develop a new spatiotemporal blind source separation (BSS) algorithm, full BSS (FBSS), by minimizing the entropy rate of separated sources. FBSS provides more flexibilities...
It has been shown that using minimum error entropy as the cost function leads to important performance gains in adaptive filtering, especially when the Gaussianity assumptions on the error distribution do not hold. In this paper, we show that by using the entropy bound rather than the entropy, we can derive an efficient algorithm for supervised training. We demonstrate its effectiveness by a system...
We present a new (differential) entropy estimator where the maximum entropy bound is used to approximate the entropy given the observations, and is computed using a numerical procedure. The resulting accurate estimate for the entropy is used to derive a new algorithm to perform independent component analysis (ICA). The new algorithm, ICA by entropy bound minimization (ICA-EBM), adopts a line search...
Because there are lots of random and fuzzy uncertainty factors in power system, the certainty model used to be adopted in reliability research were not reasonable. But cloud models theory is a powerful tool to convert numerical quantitative analysis to conceptual qualitative analysis. In this paper on the basis of introduction of cloud models, the parameter and load cloud models in actual operation...
In this paper, we present a low power strategy for test data compression that is called ldquobreak-independent-table (BIT) encodingrdquo. In addition, we present a new decompression scheme for test vectors that is called ldquotest slice difference techniquerdquo to solve huge test data volume that must be stored in the tester memory. About how reducing power dissipation problem, we present an extremely...
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