1) resultant minimum polynomial
结最小多项式
1.
The present paper deals with the relations of resultant matrices and resultant polynomials with solving the greatest common factor of two variable polynomials, respectively, on the basis of the concepts of resultant minimum polynomials and standard resultant base solving matrix introduced from the properties of resultant matrices and resultant polynomials.
应用结矩阵和结多项式的性质， 通过引入结最小多项式和标准结基解矩阵等概念， 探讨结矩阵、结多项式与求解二元多项式最大公因式的关系。
2) minimum polynomial
最小多项式
1.
The methods of elementary transcendental for solving minimum polynomial;
矩阵最小多项式的初等变换法
2.
A method using elementary transformation for calculating minimum polynomials of matrices and vectors are given.
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 。
3) minimal polynomial
最小多项式
1.
Solving process of minimal polynomial of the matrix equation;
矩阵方程的最小多项式解法
2.
In order to obtain a polynomial of less degree,the structure of Drazin inverse of matrix is analysed by using the theory of Jordan canonical matrix,and a computational method for polynomial d(λ) of least degree is given by using coefficients of minimal polynomial of matrix such that d(A) is Drazin inverse of A.
为降低多项式的次数,利用Jordan标准形理论分析了矩阵Drazin逆的结构,再由矩阵最小多项式的系数,给出了一个最低次多项式d(A)的算法,使d(A)为的Drazin的逆。
4) least polynomial
最小多项式
1.
In this paper a necessary and sufficient condition of V = AVA (0)is given by using the least polynomial of linear transformation A.
文章利用最小多项式来讨论线性空间的分解,给出线性空间是值域与核的直和(即V=AVA-1(0))的一 个充分必要条件:x是A的最小多项式m(x)的不超过一次的因式;并将此结果作了推广。
2.
The least polynomial, determinant, Smith canonical form of AA(1) are also given .
给出了广义逆A+的一种计算方法及AA(1)的最小多项式、行列式、Smith标准形等。
3.
The Jordan canonical form, characteristic value, characteristic vector, and the least polynomial of the generalized Drazin inverse matrix Ad of n th matrix A are discussed.
讨论了n阶方阵A的广义逆Ad的Jordan标准形,特征值和特征向量,最小多项式等。
6) minimal polynomial basis
最小多项式基
1.
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.
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。
补充资料：最小零偏差多项式
最小零偏差多项式
polynomial least deviating from zero
最小零偏差多项式[卯l”nl血1 least山viati吃f枷~;”a，，Me“ee加旧10”:。川“盛c，oT“”，M“oro，“eoJ 在空间CI“，b]或L，〔a，b]中具有最小范数的首项系数为l的。次代数多项式. n.月.ue6月meB在艺l}中证明:在形如 Q，，(x)=戈”+a‘x”一’十…十a，.(1)的所有多项式中，多项式 。「b一。〕”「2，一“一b〕1.(戈I=匕l—IC〔万儿arC COSI—l L，」LD一a」是空间C【“，b1中具有最小范数的唯一多项式，且其范数为 }，:，:，，。，“.。，一}宁i”·多项式 U。(x)= _「占一a]”+’:访((;:+z)a二cos(Zx一a一乃、/(n一al、二，l二二-一二七l止竺型二匕入竺二石址公竺兰二艺匕二二二二一二乙一 一L4」丫(b一x)(x一a)是L，l“，b]上(在所有形式(l)的多项式中)唯一与零偏差最小的多项式，其范数为 J「b一。飞二1 }、。。.}:，;，八)一‘L上-不竺一」在L，fa，bJ中，l
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参考词条