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1)  discrete normal divisor
离散正规子群
2)  discrete subgroup
离散子群
1.
For a general discrete subgroup in .
对的一般离散子群,运用另一方法解决了范数级数收敛性的问题。
2.
These notes provide an introduction to some aspects of the analytic theory of automorphic forms on G=SL(R),or the upper half-plane X with respect to a discrete subgroupΓ of G of finite covolume.
本讲义是关于自守形式解析理论的导论,这些自守形式定义在上半平面上,对应的群是G=SL2(R)或是G的具有有限余维数的离散子群Γ。
3)  normal subgroup
正规子群
1.
Character of group which only have n nontrivial normal subgroups
仅含n个非平凡正规子群的群的特征
2.
By using algebra of fixed point class to determine the component factors and properties of normal subgroup H of the fundamental group of the covering space, the paper studies the relation of fixed point class with fixed point class H.
本文利用不动点类的代数化 ,决定复迭空间的基本群的正规子群H的构成因素及其性质 ,研究不动点类与H不动点类的关系。
3.
Based on the Rough theory, a rough subgroup with respect to a normal subgroup of a group is discussed, and some properties of the lower and the upper approximations in a group are studied.
基于粗糙集理论 ,对一个群的子集关于正规子群的粗糙近似子群作了探讨 ,并研究了一个群的上、下近似的性
4)  normal subgroups
正规子群
1.
Su Xiang Ying and Wang Pin Chao obtained some sufficient conditions of supersoluble groups by studying semi normal subgroups of finite groups[1,2,7].
文献 [1 ]引入的半正规子群 ,对有限群结构有重要的影响 [1 ,2 ,7] 。
2.
Considering the subnormal subgroups,some equivalent conditions for nilpotency of finite groups are given and a sufficient condition for nilpotency of finite groups is obtained.
研究次正规子群对有限群结构的影响,得到幂零群的若干等价条件和一个充分条件。
5)  discrete particle swarm
离散粒子群
1.
Optimization model of development cost based on discrete particle swarm algorithm;
基于离散粒子群算法的研制费用优化模型
2.
Adaptive radial basis function neural network model based on discrete particle swarm optimization algorithms;
一种基于离散粒子群的自适应径向基网络模型
3.
Multiple optimization strategies for improving hybrid discrete particle swarm
改进混合离散粒子群的多种优化策略算法
6)  discrete particle swarm optimization algorithm
离散粒子群
1.
This paper presents a new current learning adaptive hybrid discrete particle swarm optimization algorithm for NP-hard combinatorial optimization problem and particle swarm discretization problem.
针对NP-hard组合优化及粒子群算法离散化问题,提出一种当代学习自适应混合离散粒子群算法对其进行求解。
补充资料:离散
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