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时间序列的经验模态频率分解EMFD   总被引:1,自引:1,他引:0  
在经验模态分解的基础上,提出了经验模态频率分解.经验模态频率分解是正交分解,有很好的性质和频率意义.  相似文献
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提出一种从DLffing振子产生的混沌信号中提取谐波分量的方法.依据任何信号由不同的同有简单振动模态组成的概念,利用经验模式分解(EMD)方法,将混沌信号分离为不同的内在模态函数(IMF),并在特定参数下从中分解出单一频率成分的谐波信号,从而成功地将混沌信号和谐波分甚分离.仿真实验都表明该方法非常有效.  相似文献
3.
通过仿真实验将小波变换和经验模态分解(EMD)方法分解信号的能力进行了比较,并将这种滤波特性应用于旋转机械的故障诊断中,结合包络谱分析,比较了两者对于滚动轴承内圈故障的诊断效果.仿真及轴承实验结果表明EMD方法在滤波的自适应性、分解结果的准确性以及诊断效果等方面均具有优势,更重要的是它分离出的主要分量物理意义明确,反映了信号的真实内涵.  相似文献
4.
We present algorithms for finding a longest common increasing subsequence of two or more input sequences. For two sequences of lengths n and m, where m?n, we present an algorithm with an output-dependent expected running time of and O(m) space, where ? is the length of an LCIS, σ is the size of the alphabet, and Sort is the time to sort each input sequence. For k?3 length-n sequences we present an algorithm which improves the previous best bound by more than a factor k for many inputs. In both cases, our algorithms are conceptually quite simple but rely on existing sophisticated data structures. Finally, we introduce the problem of longest common weakly-increasing (or non-decreasing) subsequences (LCWIS), for which we present an -time algorithm for the 3-letter alphabet case. For the extensively studied longest common subsequence problem, comparable speedups have not been achieved for small alphabets.  相似文献
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本文针对正弦渡用经验模式分解(EMD)进行分析时存在的问题,从实验上结出了采样率和信号间相互作用对END的影响。为了提高对极值点采样的准确性,本文提出了利用抛物线插值来拟舍极值点的方法,使结果得到明显的改善。本文还对信号间相互作用的问题进行了讨论。  相似文献
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基于脑电信号非平稳、复杂、信噪比低的特性,使用经验模式分解(EMD)算法对脑电信号进行分解,提取主要IMF分量的特征值,之后使用模糊C-均值(FCM)进行分类,并与现有的几种脑电分类方法做了对比研究.研究结果表明,基于2003年第二届BCI大赛脑电信号库的分类正确率达到78%,对于现有的脑电分类方法有一定的借鉴意义.  相似文献
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This paper develops a theory of harmonic analysis on spaces with tree metrics, extending previous work in this direction by Gavish, Nadler and Coifman (2010) [30] and Gavish and Coifman (2011, 2012) [28], [29]. We show how a natural system of martingales and martingale differences induced by a partition tree leads to simple and effective characterizations of the Lipschitz norm and its dual for functions on a single tree metric space. The restrictions we place on the tree metrics are far more general than those considered in previous work. As the dual norm is equal to the Earth Mover's Distance (EMD) between two probability distributions, we recover a simple formula for EMD with respect to tree distances presented by Charikar (2002) [36].We also consider the situation where an arbitrary metric is approximated by the average of a family of dominating tree metrics. We show that the Lipschitz norm and its dual for the tree metrics can be combined to yield an approximation to the corresponding norms for the underlying metric.The main contributions of this paper, however, are the generalizations of the aforementioned results to the setting of the product of two or more tree metric spaces. For functions on a product space, the notion of regularity we consider is not the Lipschitz condition, but rather the mixed Lipschitz condition that controls the size of a function's mixed difference quotient. This condition is extremely natural for datasets that can be described as a product of metric spaces, such as word-document databases. We develop effective formulas for norms equivalent to the mixed Lipschitz norm and its dual, and extend our results on combining pairs of trees.  相似文献
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