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基于变分模态分解的宽频信号估计算法 被引量:1
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作者 符玲 郭颖 +2 位作者 李红艳 熊思宇 李小鹏 《电网技术》 北大核心 2025年第2期748-758,共11页
随着新能源并网的发展,电网宽频振荡频发,且具有频率范围宽、模态分量多等特点。而现有的宽频信号估计方法由于存在忽略各基波动态变化、未能很好降低分量间的相互干扰等情况而无法提供准确的宽频振荡相关参数信息。因此,该文提出一种... 随着新能源并网的发展,电网宽频振荡频发,且具有频率范围宽、模态分量多等特点。而现有的宽频信号估计方法由于存在忽略各基波动态变化、未能很好降低分量间的相互干扰等情况而无法提供准确的宽频振荡相关参数信息。因此,该文提出一种考虑基波动态、降低相互干扰的宽频信号估计方法,以实现信号参数的高精度辨识,为宽频振荡分析、扰动溯源定位等应用提供数据支撑。首先,利用变分模态分解(variational mode decomposition,VMD)提取宽频信号中多种模态分量的波形信息以及对应的中心频率;其次,考虑到实际电力系统中基波频率的动态变化,利用离散傅里叶变换(discrete fourier transform,DFT)跟踪基波分量的实际频率,并以此修正基波中心频率;最后,将中心频率、模态分量波形等信息代入动态相量模型,实现宽频信号参数估计。在频率线性变化、频率动态调制、噪声等工况下验证算法性能,仿真结果表明,所提算法能更准确地获取宽频信号的参数信息,保持总相量误差(total vector error,TVE)低于3%。 展开更多
关键词 宽频振荡 参数估计 变分模态分解(VMD) 基波动态
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Fluctuation with dust of de Sitter ground state of scalar-tensor gravity 被引量:1
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作者 TANG YanKe ZHANG HongSheng +1 位作者 CHEN ChiYi LI XinZhou 《Science China(Physics,Mechanics & Astronomy)》 SCIE EI CAS 2014年第3期411-417,共7页
An exact de Sitter solution of scalar-tensor gravity is found in our recent work, in which the non-minimal coupling scalar is rolling along a non-constant potential. Based on this solution, a dust-filled FRW universe ... An exact de Sitter solution of scalar-tensor gravity is found in our recent work, in which the non-minimal coupling scalar is rolling along a non-constant potential. Based on this solution, a dust-filled FRW universe is explored in frame of scalar-tensor gravity in this article. The effective dark energy induced by the sole non-minimal scalar can be quintessence-like, phantom-like, and more significantly, can cross the phantom divide. The rich and varied properties of scalar-tensor gravity even with only one scalar is shown. 展开更多
关键词 scalar tensor gravity de Sitter space dark energy phantom divide
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Wavelet Variance Analysis of EEG Based on Window Function 被引量:3
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作者 ZHENG Yuan-zhuang YOU Rong-yi 《Chinese Journal of Biomedical Engineering(English Edition)》 2014年第2期54-59,共6页
A new wavelet variance analysis method based on window function is proposed to investigate the dynamical features of electroencephalogram(EEG).The exprienmental results show that the wavelet energy of epileptic EEGs a... A new wavelet variance analysis method based on window function is proposed to investigate the dynamical features of electroencephalogram(EEG).The exprienmental results show that the wavelet energy of epileptic EEGs are more discrete than normal EEGs, and the variation of wavelet variance is different between epileptic and normal EEGs with the increase of time-window width. Furthermore, it is found that the wavelet subband entropy (WSE) of the epileptic EEGs are lower than the normal EEGs. 展开更多
关键词 wavelet variance EEG wavelet subband entropy (WSE) window function
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