We propose the quadratic constrained formulas for the design of linear phase cosine modulated paraunitary filter banks given in references . Using these formulae, we can, directly, optimize the prototype filter coeff...We propose the quadratic constrained formulas for the design of linear phase cosine modulated paraunitary filter banks given in references . Using these formulae, we can, directly, optimize the prototype filter coefficients in a quadratic form. A design example is also given to demonstrate these formulae in this paper.展开更多
针对间歇采样转发干扰产生的假目标和目标高速运动产生的多普勒频移导致雷达脉压性能急剧下降的问题,提出一种高多普勒容限的线性调频离散相位编码(linear frequency modulation-discrete phase coding,LFM-DPC)复合调制相干波形集设计...针对间歇采样转发干扰产生的假目标和目标高速运动产生的多普勒频移导致雷达脉压性能急剧下降的问题,提出一种高多普勒容限的线性调频离散相位编码(linear frequency modulation-discrete phase coding,LFM-DPC)复合调制相干波形集设计方法。在一定多普勒频移范围内,以最小化未转发信号自模糊函数旁瓣能量以及未转发信号与转发信号互模糊函数能量建立优化模型,并设计一种基于KKT(Karush-Kuhn-Tucker)最优性条件的迭代算法对模型求解。仿真实验表明,相比于遗传算法和单一调制的LFM和DPC信号,基于KKT最优性条件的交替迭代优化算法优化的LFM-DPC波形集有更好的抗间歇采样转发干扰性能。展开更多
针对电力机车牵引变流器中故障率最高的单相脉宽调制(pulse width modulation,PWM)整流器,提出一种流形学习算法融合多域特征的故障诊断方法。根据整流器在不同工作状态下的时域、频域和时频域特征构建多域特征向量;采用Hessian局部线...针对电力机车牵引变流器中故障率最高的单相脉宽调制(pulse width modulation,PWM)整流器,提出一种流形学习算法融合多域特征的故障诊断方法。根据整流器在不同工作状态下的时域、频域和时频域特征构建多域特征向量;采用Hessian局部线性嵌入(Hessian local linear embedding,HLLE)算法融合多域特征,根据故障样本数和聚类结果,解决高维数据中固有维数和最近邻数选取困难的问题,得到用于描述故障特征的最优低维特征向量,减少特征之间的冲突和冗余;采用支持向量机进行模式识别,实现对整流器的故障诊断。结果表明:对不同的输出电压,不同的训练和测试比,15种故障模式均具有较高的诊断率。与其他方法相比,本文方法具有较好的融合效果和较强的鲁棒性。展开更多
We use the first arrival traveltime to correct the phase distortion in a nonlinear wave equation inversion scheme.This improves the precision of tomographic reconstruction of a velocity structure with large variations...We use the first arrival traveltime to correct the phase distortion in a nonlinear wave equation inversion scheme.This improves the precision of tomographic reconstruction of a velocity structure with large variations and helps solve the ill-posed problem of wave equation inversion.When the variation of the velocity distribution is large,general non-linear wave equation inversions are very ill-posed and for such strong nonlinear we can not obtain a correct inversion.One of main reasons is that the calculated and observed phase of the wavefield differs greatly if the initial model is far from the true model.This leads to highly mismatched phase between the calculated and the observed wave field.This is so-called"Cycle Skipping"problem in the full waveform inversion.The phase mismatch is even more pronounced if a high operating frequency is employed in order to increase resolution.To address this problem,we use the first arrival to"demodulate"the wave field in the frequency domain with a goal of restoring the phase of wave field.Then we minimize an objective function consisting of so called"demodulated"wave field to solve wave equation inversion problem.In this way,we find that the inversion is much improved,and when the velocity perturbation in a complicated model reaches 35%,we can still obtain a good inversion.A computer simulation shows that our method is very robust for acoustical wave inversion with good reconstruction precision.展开更多
文摘We propose the quadratic constrained formulas for the design of linear phase cosine modulated paraunitary filter banks given in references . Using these formulae, we can, directly, optimize the prototype filter coefficients in a quadratic form. A design example is also given to demonstrate these formulae in this paper.
文摘针对间歇采样转发干扰产生的假目标和目标高速运动产生的多普勒频移导致雷达脉压性能急剧下降的问题,提出一种高多普勒容限的线性调频离散相位编码(linear frequency modulation-discrete phase coding,LFM-DPC)复合调制相干波形集设计方法。在一定多普勒频移范围内,以最小化未转发信号自模糊函数旁瓣能量以及未转发信号与转发信号互模糊函数能量建立优化模型,并设计一种基于KKT(Karush-Kuhn-Tucker)最优性条件的迭代算法对模型求解。仿真实验表明,相比于遗传算法和单一调制的LFM和DPC信号,基于KKT最优性条件的交替迭代优化算法优化的LFM-DPC波形集有更好的抗间歇采样转发干扰性能。
文摘针对电力机车牵引变流器中故障率最高的单相脉宽调制(pulse width modulation,PWM)整流器,提出一种流形学习算法融合多域特征的故障诊断方法。根据整流器在不同工作状态下的时域、频域和时频域特征构建多域特征向量;采用Hessian局部线性嵌入(Hessian local linear embedding,HLLE)算法融合多域特征,根据故障样本数和聚类结果,解决高维数据中固有维数和最近邻数选取困难的问题,得到用于描述故障特征的最优低维特征向量,减少特征之间的冲突和冗余;采用支持向量机进行模式识别,实现对整流器的故障诊断。结果表明:对不同的输出电压,不同的训练和测试比,15种故障模式均具有较高的诊断率。与其他方法相比,本文方法具有较好的融合效果和较强的鲁棒性。
基金supported by the Seismic Tomography Project of Stanford University,a research consortium sponsored by companies of the oil and gas industry
文摘We use the first arrival traveltime to correct the phase distortion in a nonlinear wave equation inversion scheme.This improves the precision of tomographic reconstruction of a velocity structure with large variations and helps solve the ill-posed problem of wave equation inversion.When the variation of the velocity distribution is large,general non-linear wave equation inversions are very ill-posed and for such strong nonlinear we can not obtain a correct inversion.One of main reasons is that the calculated and observed phase of the wavefield differs greatly if the initial model is far from the true model.This leads to highly mismatched phase between the calculated and the observed wave field.This is so-called"Cycle Skipping"problem in the full waveform inversion.The phase mismatch is even more pronounced if a high operating frequency is employed in order to increase resolution.To address this problem,we use the first arrival to"demodulate"the wave field in the frequency domain with a goal of restoring the phase of wave field.Then we minimize an objective function consisting of so called"demodulated"wave field to solve wave equation inversion problem.In this way,we find that the inversion is much improved,and when the velocity perturbation in a complicated model reaches 35%,we can still obtain a good inversion.A computer simulation shows that our method is very robust for acoustical wave inversion with good reconstruction precision.
