具有马尔可夫输入的Boyer-Moore-Horspool启发式算法

R. Smythe
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引用次数: 10

摘要

Boyer-Moore-Horspool字符串匹配启发式算法是一种在随机文本中定位固定模式出现的算法。Mahmoud, Smythe, and rsamgnier [Random Struct Alg 10(1997), 169-186]在假设文本是一个独立且同分布的字符序列的情况下,研究了该算法的概率行为。这里,我们在假设文本是由不可约马尔可夫链生成的情况下,得到了类似的结果。利用一个自然的马尔可夫更新过程结构来获得比较次数的渐近行为。在适当的归一化条件下,证明了比较次数的中心极限定理是成立的。分析完全是概率性的,不使用移位生成函数。©2001 John Wiley & Sons, Inc随机结构。Alg。中文信息学报,18,153-163,2001
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Boyer-Moore-Horspool heuristic with Markovian input
The Boyer–Moore–Horspool string-matching heuristic is an algorithm for locating occurrences of a fixed pattern in a random text. Under the assumption that the text is an independently and identically distributed sequence of characters, the probabilistic behavior of this algorithm was investigated by Mahmoud, Smythe, and Régnier [Random Struct Alg 10 (1997), 169–186]. Here, we obtain similar results under the assumption that the text is generated by an irreducible Markov chain. A natural Markov renewal process structure is exploited to obtain the asymptotic behavior of the number of comparisons. Under suitable normalization, it is shown that a central limit theorem holds for the number of comparisons. The analysis is completely probabilistic and does not use the shift generating function. © 2001 John Wiley & Sons, Inc. Random Struct. Alg., 18, 153–163, 2001
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