1) grey full-rank
灰满秩
2) Full rank
满秩
1.
The exploration for projective transformation of non-full rank and full rank;
非满秩与满秩射影变换的探索
2.
Elementary transformation method of full rank decomposition of matrix and triangular decomposition of strongly full rank matrix;
矩阵的满秩分解和强满秩矩阵的三角分解的初等变换法
3.
Its full rank reachability algorithm and realization is given.
通过对Petri网可达性的分析,给出满秩Petri网可达性算法及其实现过程,在VC++平台上对算法进行验算,并对算法运行结果进行可达性讨论;该算法为满秩Petri网可达性的判定提供了一种快速有效的求解方法。
3) full rank decomposition
满秩分解
1.
Based on the two simple alternative practical methods of the full rank decomposition and Gaussian elimintion,this paper was primarily concerning with the algorithms for some generalized invers
在两种可供选择的满秩分解方法和Gauss消元法的基础上,主要研究了某些广义逆的计算。
2.
And all of these approaches are derived from the full rank decomposition technique for the incidence matrix.
这些方法都是基于网关联矩阵的满秩分解。
3.
Based on matrix s elementary row operation remaining its column vector s linear relationship and Hermite standard form of matrix,the paper gives a simple method for solving full rank decomposition of matrix only through elementary row operation.
利用矩阵初等行变换不改变矩阵列向量组线性关系的性质,以及矩阵的Hermite标准形,给出了一种只通过初等行变换可求得矩阵满秩分解的简单方法。
4) full rank factorization
满秩分解
1.
The full rank factorization and Moore-Penrose inverse for generalized row(column) unitary symmetric matrix
广义行(列)酉对称矩阵的满秩分解及其Moore-Penrose逆
2.
The concept of row (column) transposed matrix and row (column) symmetric matrix is given,their basic property is studied,and the formula for full rank factorization and orthogonal diagonal factorization of row (column) symmetric matrix are presented,which can reduce dramatically the amount of calculation and save the CPU time and memory without loss of any numerical precision.
提出了行(列)转置矩阵与行(列)对称矩阵的概念,研究了其性质,给出了行(列)对称矩阵的满秩分解和正交对角分解公式,极大地减少了行(列)对称矩阵的满秩分解和正交对角分解的计算量与存储量,且没有降低数值精度。
3.
In addition,the formulas of the full rank factorization,rank factorization and generalized inverse of row (column) antisymmetric matrix are given,which make calculation easier and accurate.
利用分块矩阵理论获得了许多新的结果,给出了行(列)反对称矩阵的满秩分解、秩分解和广义逆的公式及快速算法。
5) full rank matrix
满秩矩阵
1.
The way to determine the reflexive g-inverse of full rank matrix A was discussed.
讨论了当矩阵A为满秩矩阵时求其反射g-逆的方法,并将此方法推广,给出当A为非满秩矩阵时求反射g-逆的一般方法,同时对每一种情况给出了具体的算例。
2.
Secondly,the randomly generating of full rank matrix and per-muta.
研究了其它线性分组码用于构造M公钥体制的可行性;分析了M公钥体制中、、是保密的,实现随机选取、、成为了建立M公钥体制的关键;分析了满秩矩阵和置换矩阵的随机产生问题,并得到了一些重要结果;这些结果不仅对M公钥体制是适用的,而且对其它纠错码体制和方案也同样是有用的。
3.
This paper discusses the way about how to get the reflexive general inverse matrix of a full rank matrix A, and generalize this way, gives the general way for not full rank matrix.
讨论了当矩阵A为满秩矩阵时求其广义逆的一种方法,并将此方法推广,给出当A为非满秩矩阵时求其广义逆的一般方法,同时给出算例。
补充资料：对雪奉饯任城六父秩满归京
【诗文】：
龙虎谢鞭策，鹓鸾不司晨。君看海上鹤，何似笼中鹑。
独用天地心，浮云乃吾身。虽将簪组狎，若与烟霞亲。
季父有英风，白眉超常伦。一官即梦寐，脱屣归西秦。
窦公敞华筵，墨客尽来臻。燕歌落胡雁，郢曲回阳春。
征马百度嘶，游车动行尘。踌躇未忍去，恋此四座人。
饯离驻高驾，惜别空殷勤。何时竹林下，更与步兵邻。
【注释】：
【出处】：
全唐诗：卷175_14
龙虎谢鞭策，鹓鸾不司晨。君看海上鹤，何似笼中鹑。
独用天地心，浮云乃吾身。虽将簪组狎，若与烟霞亲。
季父有英风，白眉超常伦。一官即梦寐，脱屣归西秦。
窦公敞华筵，墨客尽来臻。燕歌落胡雁，郢曲回阳春。
征马百度嘶，游车动行尘。踌躇未忍去，恋此四座人。
饯离驻高驾，惜别空殷勤。何时竹林下，更与步兵邻。
【注释】：
【出处】：
全唐诗：卷175_14
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条