1) measure of diversity
离散量
1.
Predicting Enzyme Subclass Based on the Method of Measure of Diversity;
基于离散量算法预测酶的亚类
2.
Firstly,based on information theory,a basic concept of measure of diversity is given and an inequality about measure of diversity is proved.
基于信息理论给出了离散量的基本概念,讨论并证明了离散量的一个基本不等式,进而给出了离散增量的概念。
3.
Three increments of diversity between the measure of diversity D(X_e), D(X_i), D(X_s) and D(X) derived from one sequence in the standard set or the test set are respectively calculated.
在统计分析的基础上,选取21种三联体的概率,作为信号参数,并以这些参数分别构建内含子、外显子和基因间序列的离散源,计算了离散量。
2) discrete magnitude
离散量
1.
This paper analyses the directive function of the dialectical transforming from discrete magnitude into continuous quantity in building the logarithm by Napiel and the calculus by Leibnitz,thus embodying the historic feats of the mathematical analogism in the mathematical discovery.
分析了从离散量到连续量的辩证转化在纳白尔建立对数和莱布尼兹建立微积分过程中的指导作用。
3) discrete quantity
离散量
1.
In this paper it discusses the method of how to count the numbers of aerosol particles through using many-corridors discrete quantity gathering system.
讨论了运用多道离散量数据采集系统 ,对微粒子进行检测的方
2.
In this paper, we present the number sequence method which can treat accurately with continuous quantity and discrete quantity solving questions in mathematic analysis and some applied examples from different aspects.
给出了在数学分析解(证)题中,如何正确处理连续量与离散量的方法———“点列(数列)法”,并从几个方面例说了该方法在数学分析解(证)题中的一些应用。
4) discrete variable
离散变量
1.
Network iterative optimization of virtual n-dimensional discrete variables;
拟n维离散变量网格迭代优化方法
2.
Study on discrete variables optimization design for heliocentric-type reducer based on simulated annealing algorithm;
基于SA算法的行星齿轮减速器离散变量优化设计
3.
Superficial talking on optimum structure design of discrete variable with improving method;
浅谈离散变量改进算法的结构优化设计
5) discrete variables
离散变量
1.
How to determine discrete variables in structural optimization by neutral networks and genetic algorithm;
遗传算法和神经网络组合求解离散变量结构优化问题
2.
Chaotic genetic algorithm for structural optimization with discrete variables;
离散变量结构优化设计的混沌遗传算法
3.
Engineering structure s discrete variables optimum desig nunder multiple loading conditions;
工程结构的多工况离散变量优化设计
6) increment of diversity
离散增量
1.
Application of immune classifier based on increment of diversity in model species genomes
基于离散增量的免疫分类器在模式生物基因中应用
2.
The new information coefficient improved the increment of diversity and could be applied to cluster analysis.
这一新的信息系数较离散增量信息系数有所改进,并可应用于聚类分析。
3.
Based on this inequality,a concept of increment of diversity is discussed and a defined.
基于信息理论给出了离散量的基本概念,讨论并证明了离散量的一个基本不等式,进而给出了离散增量的概念。
补充资料：离散时间周期序列的离散傅里叶级数表示
(1)
式中χ((n))N为一离散时间周期序列，其周期为N点，即
式中r为任意整数。X((k))N为频域周期序列，其周期亦为N点，即X(k)=X(k+lN)，式中l为任意整数。
从式(1)可导出已知X((k))N求χ((n))N的关系
(2)
式(1)和式(2)称为离散傅里叶级数对。
当离散时间周期序列整体向左移位m时,移位后的序列为χ((n+m))N，如果χ((n))N的离散傅里叶级数(DFS)表示为,则χ((n+m))N的DFS表示为
式中χ((n))N为一离散时间周期序列，其周期为N点，即
式中r为任意整数。X((k))N为频域周期序列，其周期亦为N点，即X(k)=X(k+lN)，式中l为任意整数。
从式(1)可导出已知X((k))N求χ((n))N的关系
(2)
式(1)和式(2)称为离散傅里叶级数对。
当离散时间周期序列整体向左移位m时,移位后的序列为χ((n+m))N，如果χ((n))N的离散傅里叶级数(DFS)表示为,则χ((n+m))N的DFS表示为
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