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hypercubes相关的网络例句

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

Several invariants of star graphs and hypercubes, such as Mobius cubes, arrangement graphs,-star graphs, split star graphs, cluster-star graphs, alternating group graphs are advantageous over n-cube in many aspects.

近几年内,除了超立方体之外,有许多类似星状图和超立方体的多处理机架构被提出来讨论,其中较具代表性的有:Mobius cubes、排列图、-星图(n,k-star graphs 、分星图、聚星图(Clustered-star graphs)、变换群图等。

Interconnection networks; fault-tolerant embedding; Mbius cubes; hypercubes; star graphs; arrangement graphs-star graphs; split star graphs; cluster-star graphs; alternating group graphs

中文关键字连结网路;容错嵌入;超立方体; Mbius cubes、星状图;排列图;星图;分星图;变换群图

As one solution, an alternative topology based on HyperCubes (Schlosser et al., 2005) can be employed.

作为一种解答,供选择的拓扑结构根据HyperCubes (Schlosser 等, 2005)可能被使用。

We study firstly the SFD on the multi-ring system and the hypercubes system with arbitrarily absent links.

本文首次研究了多环系统及缺少任意条边的不完全超立方体的系统级故障诊断问题。

The algorithm can get the access relation between data hypercubes by using their priori frequency and similarities.

经过性能模拟发现SMDPA算法在一般访问模式下依然能得到良好的平衡和并发性能。

So, scholars proposed LogCube and FullCube which is based on logical HyperCube. they eliminated the complete HyperCubes limit and improved the performance of structure, while they still have biggish limitations.

为此,人们提出了LogCube、FullCube等逻辑超立方体结构,它们消除了HyperCube的局限性,提高了结构的性能,但仍存在较大的缺陷。

Design of Experiments: Full Factorial, Monte Carlo, Parameter Study, one-at-a-time, Orthogonal Arrays, Latin Hypercubes

实验设计:全阶乘,蒙特卡罗,参数学习,一次一个,正交矩阵,拉丁超立方体

In the present paper, three well-known networks, hypercubes, de Bruijn and Kautz, are considered and the values of AdD and BdD are determined, which show AdD = BdD.

本文考虑D为超立方体网络、De Btuijn网络和Kautz网络,对d的不同值确定了AdD及BdD,而且均有AdD=BdD。

When a node in hypercubes consists of a main procesor and a communication coprocessor, link fault model is more adequate for routing in injured hypercubes.

本文在研究了各种有关选路算法的基础上,提出了三种具有不同特点的容错选路算法:局部启发式容错选路算法[128,129],全局引导式容错选路算法和双向搜索式容错选路算法[130]。

In the conventional CMAC learning scheme, the correcting amounts of errors are equally distributed into all addressed hypercubes, regardless the credibility of those hypercubes. The proposed improved learning approach uses the learned times of the addressed hypercubes as the credibility of the learned values.

在常规的CMAC中,误差的校正值被平均地分配给所有启动存储单元,而不管这些存储单元的可信度;在改进的CMAC中,利用激活单元先前学习次数作为可信度,其误差校正值与激活单元先前学习次数的负k次方成比例。

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