maximal ideal

maximal ideal的基本解释

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极大理想

与maximal ideal相关的网络例句 [注：此内容来源于网络，仅供参考]

The first chapter, main instead " duo-ring " condition of " every maximal left ideal is GW-ideal " condition,study strongly regularities of GP-V-ring on this condition.lt is shown that (1) R is strongly regular iff R is left GP-V-ring whose maximal left ideals are GW-ideal.(2)R is strongly regular iff R is left GP-V-ring whose maximal right ideals are GW-ideal. The second chapter, generalize some results of GP-V-ring to GP-V-ring, discuss regularity of GP-V-ring.It is shown that (1) R is left self-injective regular with non-zero socle iff R is left GP-V -ring with Soc = Soc and R contains an injective maximal left ideal.(2)R is regular ring and every maximal essential left ideal is ideal iff R is left GP-injective left GP-V -ring and every maximal essential left ideal is ideal.

第一章主要将"duo-环"条件替换成"每一极大左理想是GW-理想"条件，研究在此条件下，GP-V-环的强正则性，证明了：(1)R是强正则环当且仅当R是左GP-V-环且R的每一极大左理想是广义弱理想；(2)R是强正则环当且仅当R是左GP-V-环且R的每一极大右理想是广义弱理想，第二章，主要将GP-V-环上一些结果推广到GP-V′-环上，讨论GP-V′-环的正则性，证明了：(1)R是左自内射正则环且Soc≠0当且仅当R是包含内射极大左理想的GP-V′-环，且Soc=Soc；(2)R是正则环且每一极大本质左理想是理想当且仅当R是左GP-内射的左GP-V′-环且每一极大本质左理想是理想。

Since any frequent itemset is a subset of a maximal frequent itemset (an itemset is maximal frequent if it has no superset that is frequent), this paper proposes the DMFI (Discovery of Maximal Frequent Itemsets) algorithm for mining all the maximal frequent itemsets from data sets. This algorithm searches the maximal frequent itemsets in data sets from both bottom-up and top-down directions in the meantime. This paper proposes an algorithm that evaluates the boundaries on the support and confidence of uncalculated itemsets by exploiting the information provided by the calculated itemsets.

本文在经典关联规则的基础上，提出了一系列扩展的关联规则开采算法：发现关联规则的难度体现在发现频繁项目集上，事实上最大频繁项目集（其所有的超集都为非频繁项目集的频繁项目集）的集合已经包含了所有的频繁项目集，本文提出一种发现最大频繁项目集的算法DMFI(Discovery Maximal Frequent Itemsets)，该算法采用自底向上和自顶向下相结合的搜索策略对数据空间进行有效的搜索。

Thirdly,quasi-normal inequalities of a-variation maximal operator and a-conditional variation maximal operator of scalar predictable tree martingales areidentified by the use of martingale transforms and by the construction of convex or concave function method;on this basis and with the help of previsiblity or regu-larity,Burkholder-Davis-Gundy\'s inequality of a-variation maximal operator and a-conditional variation maximal operator of scalar predictable tree martingales are iden-tified by the application of Hardy-Lorentz interpolation theory.At the same time,bythe use of G.

再次，应用鞅变换和构造凸或凹函数方法证明了标量值可料树鞅的α-方极大算子和α-条件方极大算子的拟范数不等式；然后，在这些拟范数不等式的基础上，应用Hardy-Lorentz空间插值方法证明了当树鞅是可控或正规树鞅时关于标量值可料树鞅α-方极大算子和α-条件方极大算子的Burkholder-Davis-Gundy's不等式成立。

与maximal ideal相关的网络解释 [注：此内容来源于网络，仅供参考]

maximal ideal：极大理想

maximal hermitian operator 最大埃尔米特算子 | maximal ideal 极大理想 | maximal ideal space 极大理想空间

maximal ideal：最大理想的

最大自由陈式 maximal free expression | 最大理想的 maximal ideal | 最大独立集合 maximal independent set

maximal ideal space：极大理想空间

maximal ideal 极大理想 | maximal ideal space 极大理想空间 | maximal operator 最大算子

regular maximal ideal：正则极大理想

regular matrix, non-singular matrix 正則行列 | regular maximal ideal 正则极大理想 | regular measure 正则测度

maximales Ideal maximal ideal：极大理想

Matrixnorm matrix norm 矩阵范数 | maximales Ideal maximal ideal 极大理想 | Maximum maximum 极大值