本文主要讨论了两类结构矩阵的逆特征值问题。
In this paper, two kinds of structure inverse eigenvalue problems are discussed.
推导了以顺波、逆波为状态向量的应力波传播方程和杆形部件的作用力、速度传播的特征矩阵；
Stress wave propagation equations that incident wave and reflection wave are condition vectors are derived from three discrete forms as well as the characteristic matrix of the force and the velocity.
最后，浅谈了矩阵逆特征值问题的应用。
Finally, we simply talk about the application and development of inverse eigenvalue problem.
在结构设计、振动系统、自动控制、矩阵对策等领域中存在各种各样的矩阵逆特征值问题及广义逆特征值问题。
There are all kinds of inverse eigenvalue and generalized inverse eigenvalue problems in the fields of structural design, vibration system, automation control and matrix decision etc.
本文对一类特殊矩阵的逆矩阵和特征值问题进行了研究，并得出了一个求该类矩阵的逆的一个公式，用该公式求这类矩阵的逆比用现有的方法要简单的多。
In this paper, an inversion and Eigenvalue problem of a matrix are studied, and a formula of matrix inversion which is much simpler than the existing methods is put out.
对给定的特征值和对应的特征向量，提出了对称正交对称半正定矩阵逆特征值问题及最佳逼近问题。
From given eigenvalues and eigenvectors, the inverse eigenvalue problem of symmetric ortho-symmetric positive semi-definite matrices and its optimal approximate problem were considered.
刻划了特征不为2及3的域上的上三角矩阵空间保逆矩阵的可逆加法算子的形式。
The authors characterize the forms of additive invertable operators preserving inverse matrix of the upper triangular matrix space over a field which characteristic is not 2 or 3 .
利用矩阵的极分解，导出了逆特征值问题的最佳逼近解。
The optimal approximate solution of this inverse eigenvalue problem also was given by means of the polar decomposition of matrices.
由目标的实测数据，计算特征向量总体的均值和协方差矩阵及其逆矩阵，由距离判别法进行目标识别。
The mean and covariance matrixes and their inverse matrixes of all eigen vectors are obtained through measured data of the target. And the target is recognized by techniques of range discrimination.
由目标的实测数据，计算特征向量总体的均值和协方差矩阵及其逆矩阵，由距离判别法进行目标识别。
The mean and covariance matrixes and their inverse matrixes of all eigen vectors are obtained through measured data of the target. And the target is recognized by techniques of range discrimination.
应用推荐