正交矩阵

正交矩阵特征值问题的最佳向后扰动分析与一类特征子空间的Rice条件数

The Optimal Backward Perturbation Analysis for Orthogonal Matrix Eigenvalue Problem and Rice Condition Numbers of Certain Characteristic Subspaces

多小波的平衡处理就是对低通滤波器P（ω）选择正交矩阵R，使得常数信号成为平衡后低通滤波器的特征信号。

For low-pass matrix filter P (ω), the orthogonal matrix R is selected to ensure the constant signal as a characteristic signal matrix filter of balanced low-pass matrix filter .

广义Fuzzy正交矩阵

The Generalized Orthogonal Fuzzy Matrices

给出r广义次正交矩阵的概念，并研究了它的性质。

The concepts of r-sub-orthogonal matrix are given , and its properties discussed .

给出了广义Fuzzy正交矩阵的概念、性质及判定，并给出了正交向量的定义。

In this paper , the definitions , some properties and judgements of the generalized orthogonal fuzzy matrices are given .

首先利用PCA将n维词语特征-文档矩阵变换为一个m维的正交矩阵，再采用RS的方法对m维新特征进行进一步的约简。

First , using PCA method transform a n-dimensional terms-documents matrix into m-dimensional orthogonal matrix . Then , a rough set method to the result of principal components analysis is used for feature reduction .

给出了由计算机随机生成正交矩阵的列主元高斯消去法、逆broyden秩1法、施密特正交化法等方法的算法描述。

Gaussian elimination with partial pivoting method and Broyden 's method and Orthogonal method for generating stochastic orthogonal matrix are presented .

它充分考虑了参数之间的约束关系，利用正交矩阵保证Frobenius范数不变性来选择约束条件。

After constraint relations between parameters are observed and studied , a constraint condition is selected using the property that orthogonal matrix ensures Frobenius norm to be unvarying .

本文给出了行正交矩阵的分层克罗内克积扩大法，以及扩大后矩阵的快速算法，利用分层克罗内克积扩大法构造了L2空间上的正交完全系。

In this paper Layer-built Kronecker Product Expansive Method of Matrix , in Which Rows Are Orthogonal Each Other and fast algorithm of expanded matrix are presented . Using this expansive method , Orthogonal Complete Systems in L2-space are built up .

给出了准正交矩阵的概念，在文[1]的基础上研究了Euclidean空间中的变换是准正交变换的几个条件，得到了准正交变换的一些新性质，推广了有关正交变换的相应结果。

In this paper , we defined Almost Orthogonal Matrix , Gave some conditions for a transformation on an Euclidean space being an Almost Orthogonal Transformations , and obtained some new properties of Almost Orthogonal Transformations , which generalize the corresponding results on Orthogonal transformations .

正交矩阵的特征多项式及特征根

On the Characteristic Polynomial and Characteristic Root of the Orthogonal Matrix

基于正交矩阵测试用例生成方法的实用策略

MATRIX CHECK-UP Study on the Practical Strategy of OATS-based Test Case Implementation

高频增益平衡法中正交矩阵的收敛定理

The Asymptotic Characteristic Theorem of Quadratic Matrix in High Frequency Gain Balance

复正交矩阵的实正交相抵标准形

Real Orthogonal Equivalence Canonical Form of Complex Orthogonal Matrix

相关免疫函数和正交矩阵的研究是等价的。

Resilient functions are constructed by applying orthogonal array .

域上与正交矩阵相似的矩阵

Matrices Which Are Similar Over Fields to Orthogonal Matrices

正交矩阵的递归生成算法

A recursive construction algorithm of the orthogonal array

强亚正交矩阵及其性质

The Strongly Sub-orthogonal Matrix and Its Properties

行正交矩阵的分层克罗内克积扩大法

Layer-built Kronecker Product Expansive Method Of Matrix , in Which Rows Are Orthogonal Each Other

亚次正交矩阵及性质

The properties of generalized sub-orthogonal matrix

正交矩阵的若干性质

Some Properties of The Orthogonal Matrix

蕴含正交矩阵的符号模式

Sign Patterns That Allow Orthogonal Matrix

k-拟次正交矩阵

The k-Generalized Sub - orthogonal Matrix

同时，对随机正交矩阵的参数表示的随机性做了的定量分析，最后的结论是以概率为1得到随机正交矩阵的参数表示。

In succession , some analysis is given out for the randomicity of the parametrized matrix .

给出了正交矩阵的相似标准形及正交矩阵的分解形式。

This paper describes the orthogonal matrix canonical forms for matrices and the orthogonal matrix decomposition form .

传统的研究从数字信号处理领域出发，认为逻辑设计中的谱变换矩阵也必须是正交矩阵。

Traditional research also concluded that spectral transform matrix should be orthogonal as in the field of DSP .

最后，在空时区块码不同的正交矩阵之下，展现出我们的模拟结果。

Finally , we present our simulation results under different encoding scheme of the space time block code .

在强亚正交矩阵的基础上，给出了次强亚正交矩阵的概念，讨论了次强亚正交矩阵的一些性质。

On the base of strongly sub-orthogonal matrix , given the concept of sub-strongly sub-orthogonal matrix , obtained its properties .

用奇异值分解的正交矩阵变换可以减少共线性的影响。

The use of orthogonal matrix transformations such as the singular value decomposition ( SVD ) can reduce the effect of collinearity .

本文用矩阵分解法给出该反问题在正定矩阵类及正交矩阵类中的通解。

General solutions of above inverse problem in positive definite matrix and in orthogonal matrix are given here by using factorization method of matrix .