最小多项式

Jordan标准形与矩阵最小多项式

Jordan Canonical Form and the Minimal polynomial of Matrix

本文中引入了有理子空间的理论尤其是最小多项式基的概念和性质，不仅能很好地解释SIMO系统的子空间算法，而且为MIMO系统盲辨识和盲均衡提供重要的理论依据。

In this paper , the theories of rational subspace and minimal polynomial basis ( MPB ) are introduced . These theories can not only explain subspace method of SIMO systems but also offer an important support to the blind identification and blind equalization of MIMO systems .

伴随阵的最小多项式和Jordan标准形

The Least Polynomial and the Jordan Canonical Form of Adjoint Matrices

广义四元数体上矩阵的最小多项式

The Minimal Polynomial of Matrix over the Generalized Quaternion Field

矩阵方程的最小多项式解法

Solving process of minimal polynomial of the matrix equation

求矩阵最小多项式的初等变换方法

The Methods of Elementary Transcendental for Solving Minimum Polynomial

求矩阵最小多项式的一种方法及其应用

A Method of Finding the Minimal Polynomial of Matrix

矩阵最小多项式求法探讨

On the Approaches to Minimal Polynomial of a Matrix

线性变换作用向量与子空间的最小多项式

The Minimal Polynomial of Vector with Linear Transform

用最小多项式求线性微分方程组的基解矩阵

A Method for Calculating Basic Solution Matrix of Linear Simultaneous Equations by Using Minimal Polynomial

关于置换矩阵的最小多项式

On the Least Polynomial of Permutation Matrix

矩阵最小多项式的性质及它的一种初等求法

Properties of the Least Polynomial of Matrix and an Elementary Method to Get Least Polynomial

有关最小多项式定理及其应用

Theorem and Application of the Least Polynomial

最小多项式的性质及其应用

Qualities and Application of the Least Polynomial

最小多项式与矩阵的对角化

The Minimal Polynomial and Matrix Opposite Angle

分别给出计算矩阵的最小多项式和向量关于矩阵的最小多项式的初等变换方法。

A method using elementary transformation for calculating minimum polynomials of matrices and vectors are given .

介绍了线性变换作用向量的化零多项式与最小多项式的概念，并讨论了它们的性质。

The concept is introduced of the annihilating polynomial and minimal polynomial of vector with linear transform , their property discussed .

利用子空间关于矩阵的最小多项式研究了矩阵可广义对角化的充要条件，给出了矩阵可广义对角化的一种算法。

Based on the pseudo-division algorithm for multivariate matrix polynomials , a new solving process of characteristic series for algebraic polynomial systems is given .

计算多项式矩阵的特征多项式或最小多项式是计算机数学领域中一个基本问题，尚缺乏有效的算法。

Computing the characteristic polynomial or the minimal polynomial of a polyno-mial matrix is a basic problem in computer algebra , but it lacks of effective algorithms .

本文介绍利用哈密尔顿&凯莱定理把矩阵A的伴随矩阵、逆矩阵表示成A的多项式方法，给出求最小多项式的方法；

A method of an accompany matrix and invertible matrix is indicated polynomial using Hamilton-Cay lay theorem is introduced . A method of calculating the smallest polynomial is given .

最后，我们给出了一种计算多项式矩阵最小多项式或特征多项式的有效算法，它从低次项到高次项逐项确定最小多项式的系数多项式。

Finally , we present an efficient algorithm for computing the minimal polynomial of a polynomial matrix . It determines the coefficient polynomials term by term from lower to higher degree .

给出矩阵A的最小多项式的定理，并举例说明了关于矩阵最小多项式的定理在解决某些问题时的有效性。

In this paper , theorem about the Least Polynomial of matrix A is given , and validity about the Least Polynomial theorem in solving certain questions is explained with examples .

利用有理子空间及最小多项式基理论，通过估计瞬时相关矩阵，辨识出信道因数，完成系统盲均衡。

By utilizing the theory about the rational subspaces and the minimal polynomial basis and then estimating the instantaneous correlation matrix , this technique can identify the channel coefficients and accomplish the blind equalization . Computer simulations can prove its effectiveness .

然后，给出了求无向网络中带有边集限制的最小树多项式时间算法；

Then we give a polynomial time algorithm to solve the minimal weight spanning tree with edge set restricted problem .

某些高维区域上的最小零偏差多项式

The polynomials with least deviation from zero in some multidimensional region

对于给定的插值结点组，寻找适定的插值多项式空间（即使插值多项式唯一存在的最小次插值多项式空间）。

To find the properly posed space of interpolating polynomials for a given set of interpolation condition .

最小网络问题及其多项式时间算法

Minimum network problem and its time-based polynomial algorithm

关系模式最小基数候选关键字多项式时间求解算法

A Polynomial-Time Algorithm to Find a Candidate Key of Minimum Cardinality on a Relation Schema

采用4点平均算法、相关算法、最小平方算法、多项式拟合系数算法、粒子群算法和主元分析法提取热波信号的幅值、相位并进行信号重构。

The 4-point average algorithm , lock-in algorithm , least squares algorithm , polynomial fitting coefficients algorithm , particle swarm algorithm and principal component analysis method for the amplitude , phase and reconstruction information are developed .