特征向量

基于多维特征向量及ANN技术的色彩传递算法

New color transferring algorithm based on multi-dimensional eigenvector and ANN searching technology

特征向量在LFSR序列分析中的应用

The Use of Eigenvector in Analyzing the Output Sequences of LFSR

基于向量相似度不断搜索问题域空间，使其不断得到进化，逐步得到Web文本的最优特征向量。

Then constantly searching the question territory space based on vector similarity to obtain the best feature vector .

在提取特征向量的基础上，建立了基于BP神经网络的故障类型分类器。

Based on the eigenvector exertion , the fault model sorter on BP neural network is constructed .

PATRAN/NASTRAN建立了Hα与白光望远镜的有限元模型，采用特征向量法求得前四阶固有频率和振型。

PATRAN / NASTRAN , and the first several orders of natural frequencies and modal shapes are calculated with eigenvectors method .

在重组的DCT系数中提取特征向量，并对其进行聚类。

Feature vectors are extracted from the re-organized DCT coefficients , and clustered .

CFV-NB：基于概念特征向量的NB文档分类模型

CFV-NB : Nave - Bayes Documents Classification Model Based on Concept Feature Vectors

多机电力系统中PSS最佳安装地点的选择&对特征向量分析法的研究

Selection for Allocations of PSS in Multimachine Power Systems : Study of Eigenvector Method

采用欧式距离来衡量特征向量之间的相关性，计算找出同类别最近的k个样本与不同类别最近的k个样本进行类间特征筛选。

Euclidean distance is used to measure the correlation between the feature vectors and calculate the k-nearest sample of the same category and the different category .

该检测算法的核心是将检测问题转化为模式识别问题，首先对接收信号建立AR模型并提取AR模型系数作为特征向量，然后利用人工神经网络对信号进行检测。

The characteristic is extracted by the AR model coefficient and then be employed to detect the target signal with ANN .

并以此特征向量作流型样本对RBF神经网络进行训练，实现流型的智能化识别。

The RBF neural network is trained using those eigenvectors as flow regime samples and the flow regime intelligent identification is realized .

设计了一种基于HSV空间改进的颜色纹理直方图，并将其作为输入特征向量，利用SVM学习分类算法进行训练。

An improved color-texture histogram is developed based on HSV color space , which is used as the input of SVM .

利用经过降维后的信号双谱特征向量来训练SVM分类器，构建了通信辐射源识别分类器。

After the dimension reduction , the signal bispectrum features vector is used to train SVM classifier and the transmitter fingerprint identification classifier is constructed .

然后利用区间K-Means算法对序列中的多维特征向量进行分割，获得初始聚类中心。

To obtain initial cluster centers , we use the regional K-means algorithm to segment the multi-dimensional feature vector sequence .

通过搜索每个lattice，从中提取所有音节和相邻音节对的声学分来形成语音文档的特征向量。

Extracting the acoustic score of syllable and syllable-pair from every spoken document by searching every syllable lattice of spoken documents to form the feature vectors of spoken documents .

AHM既不需要计算特征向量，也不需要进行一致性检验，运算量小，科学性强。

There are not eigenvector computations and uniformity test in AHM .

解决了应用SVM识别算法对遥感矿化信息提取过程中输入样本特征向量（微弱信息样本）的构造问题。

Through SVM algorithm , solving the building problem of input sample feature vector ( weak information sample ) in the process of extracting mineralizing information from RS data .

网络初始向量与已知特征向量垂直，则lyNN平衡解向量将垂直于该特征向量；

If the initial vector is perpendicular to a known eigenvector , so is the equilibrium vector .

带极端特征向量的重新开始GMRES算法

A Restarted GMRES Method Augmented with Extreme Eigenvectors

基于KLT与滑动DCT的相似关系，提出了一种新的特征向量自适应递推估计算法。

A new adaptive recursive algorithm for eigenvector estimation based on the relations between KLT and sliding DCT was presented .

针对所设计的特征向量，在传统的隐马尔柯夫模型（HMM）基础上提出了一个新的处理一维随机序列的分类器&退化隐马尔柯夫模型。

Based on the traditional HMM , we propose a new classifier & DHMM ( Degraded Hidden Markov Model ) to deal with 1D sequence .

首先对人脸进行Gabor小波变换，然后用PCA方法降低Gabor特征向量的维数。

At first , we can extract more features via Gabor wavelet transform and PCA method will contribute to reduce the dimension of Gabor feature vectors .

可以求出语音信号的LPC倒谱特征向量，该特征向量在语音信号分析中得到了广泛的应用。

Voice signal can be obtained by LPCCEP eigenvector , the eigenvector of the voice signal analysis has been widely used .

文中首先提取中心矩作为特征向量，再采用Fisher判据进一步进行特征压缩，最后利用支撑矢量机（SVM）分类算法实现识别。

A multi-class support vector machine ( SVM ) classifier is designed to classify space objects based on the selected central moments features by using Fisher linear discriminant criterion .

通过对PCA中主成分的特征向量分析，以及对原始各波段的负荷因子分析可知，PCA变换处理在澜沧江流域土地覆盖遥感监测分类实施中，对波段选取具有一定的指导作用；

Based on the analysis of feature vector and original bands loading on the main principal components , we known that PCA is of some affects about feature selection .

利用从济南地区ETM图像中提取出的灰度共生纹理特征向量和灰度共生-差分维数向量对BP神经网络和朴素贝叶斯网络进行训练，并用训练后的网络对其它地区遥感图像进行地物识别实验。

In this article gray co-occurrence vector and co-dimension feature vector extracted from ETM images of Jinan are used in recognition experiment with BP neural network and Bayesian network .

基于电极位移信号特征向量集合建立多元线性回归、多元非线性回归、RBF神经网络焊点接头强度预测模型，采用交叉有效性检验方法，检验预测模型的有效性。

Linear , nonlinear regression analysis and RBF neural network were used to predict nugget strength based on the input vector which was constructed by factors inspected of electrode displacement signal .

首先对图像进行划分，然后再对子图像使用PCA方法提取特征向量。

The method is that : in image feature extraction , first the image is divided , and then the sub image using PCA method to extract the feature vector .

据此认为，利用LPC分析提取电弧声的特征向量，建立SVM模型是一种焊接动态参数监控的可行方法。

The study indicated that forming characteristic vectors by the LPC coefficients of arc sound to build SVM pattern recognition model is a feasible way for welding parameters monitoring .

文中提出了首先用小波分析方法提取出瞬态信号的各级小波分解能量，然后再用RBF神经网络对提取的特征向量进行分类。

At first , all levels energy of wavelet decomposed in the transient are extracted by the means of wavelet analysis , then the extracted feature vectors are classified with RBF neural network .