一种数据效率最佳的同构推理算法

Q4 Mathematics
Peter A. Flangan
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引用次数: 1

摘要

给出了一种最优数据高效同构识别算法的时间、空间和数据复杂度。数据复杂性,即推理算法终止所需的数据量,被分析并显示为所有可能的同构推理算法的最小值。最小数据需求为≤log2 (n)²,并给出了一种构造该最小数据序列的方法。平均数据需求约为2 log2(n)。时间复杂度为O(n2log2(n)),空间要求为O(n2)
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An optimally data efficient isomorphism inference algorithm

The time, space, and data complexity of an optimally data efficient isomorphism identification algorithm are presented. The data complexity, the amount of data required for an inference algorithm to terminate, is analyzed and shown to be the minimum possible for all possible isomorphism inference algorithms. The minimum data requirement is shown to be ⌈log2 (n)⌉, and a method for constructing this minimal sequence of data is presented. The average data requirement is shown to be approximately 2 log2(n). The time complexity is O(n2log2(n)) and the space requirement is O(n2)

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来源期刊
信息与控制
信息与控制 Mathematics-Control and Optimization
CiteScore
1.50
自引率
0.00%
发文量
4623
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