1) wavelet packet energy eigenvector
小波包特征向量
1.
In order to diagnose the rotor fault precisely,this paper applies the resilient back propagation neural network and steepest descent back propagation neural network which based on wavelet packet energy eigenvector.
为精确诊断转子故障,采用了基于小波包能量特征向量的弹性BP神经网络和最速下降BP算法神经网络的故障诊断方法,对采集到的信号进行3层小波包分解,构造小波包特征向量,对样本进行3层BP网络训练,实现智能化故障诊断。
2) characteristics of wavelet packet energy
小波包能量特征
1.
To improve the recognition rate of sucker rod\'s defects,the composite characteristics including both the characteristics of wavelet packet energy and peak-to-peak values in time domain were applied to the recognition in combination with the SVM based on small samples.
为了提高抽油杆的缺陷识别率,将小波包能量特征和时域峰峰值特征组成的混合特征向量和基于小样本的支持向量机法应用于抽油杆的缺陷识别中。
3) wavelet-based attribute vector
小波特征向量
1.
Adequately the algorithm thinks about the grain feature of pixel and its neighborhood in brain CT image,subsequently constructs a multi-resolution wavelet-based attribute vector(WAV) of the pixel.
这种算法充分考虑了颅脑CT图像的像素点及其临域的纹理特征,通过进行小波变换建立对应于每个像素点的多分辨率小波特征向量,并以小波特征向量间的差异作为判别依据,在目标图像中标记非刚性配准所需的对应特征点。
4) WP-CE
小波包特征熵
1.
A new fault diagnosis method of vibrating of hearings was proposed on the basis of neural network based on wavelet packet-characteristic entropy(WP-CE).
提出了一种基于小波包特征熵-神经网络的轴承故障诊断新方法。
2.
It adopts three-layer wavelet packet to decompose the monitored pressure pulsation signal of draft tube, extracts WP-CE (Wavelet Packet-Characteristic Entropy), and constructs WP-CE vectors of signals, then takes those vectors as fault samples to train three-layer BP(Back Propagation) neural network, finally realizes intelligent fault .
为精确诊断水轮机尾水管涡带,该文提出一种基于小波包特征熵的神经网络故障诊断新方法。
5) vector-valued wavelet packet
向量值小波包
1.
This paper is a research on the property of compact support biorthogonal multiple vector-valued wavelet packet,and offers the algorithm of decomposition and reconstruction to the biorthogonal multiple vector-valued wavelet packet.
文章研究了紧支撑双正交多重向量值小波包的性质,并给出了相应的分解与重构算法。
2.
Finally,some new orthogonal bases for L2(Rs,Cr) are constructed from an orthogonal multivariate vector-valued wavelet packets by virtue of .
研究了高维向量值小波包的构造与性质,引进了数量矩阵伸缩的高维向量值小波包的概念。
6) vector-valued wavelet packets
向量值小波包
1.
Orthogonality of compactly supported multivariate vector-valued wavelet packets;
紧支撑多元向量值小波包的正交性
2.
The definition of multiple vector-valued wavelet packets associated with the orthogonal multiple vector-valued multivariable scaling functions and its constitutive procedure were given.
引进向量值多分辨分析,给出对应于高维多重向量值正交尺度函数的多重向量值小波包的定义及其构造方法。
补充资料：特征值和特征向量
| 特征值和特征向量 characteristic value and characteristic vector 数学概念。若σ是线性空间V的线性变换，σ对V中某非零向量x的作用是伸缩 ：σ（x）＝aζ ，则称x是σ的属于a的特征向量 ，a称为σ的特征值。位似变换σk（即对V中所有a，有σk（a）＝kα）使V中非零向量均为特征向量，它们同属特征值k；而旋转角θ（0＜θ＜π）的变换没有特征向量。可以通过矩阵表示求线性变换的特征值、特征向量。若A是n阶方阵，I是n阶单位矩阵，则称xI－A为A的特征方阵，xI-A的行列式 ｜xI－A｜展开为x的n次多项式 fA（x）＝xn－（a11＋…＋ann）xn-1＋…＋（－1）n｜A｜，称为A的特征多项式，它的根称为A的特征值。若λ0是A的一个特征值，则以λ0I－A为系数方阵的齐次方程组的非零解x称为A的属于λ的特征向量：Ax＝λ0x。L.欧拉在化三元二次型到主轴的著作里隐含出现了特征方程概念，J.L.拉格朗日为处理六大行星运动的微分方程组首先明确给出特征方程概念。特征方程也称永年方程，特征值也称本征值、固有值。固有值问题在物理学许多部门是重要问题。线性变换或矩阵的对角化、二次型化到主轴都归为求特征值特征向量问题。每个实对称方阵的特征根均为实数。A.凯莱于19世纪中期通过对三阶方阵验证，宣告凯莱-哈密顿定理成立，即每个方阵A满足它的特征方程，fA(A)＝An－(a11＋…＋ann)An-1＋…＋(－1)n｜A｜I＝0。 |
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