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基于状态压缩的最长公共上升子序列快速算法
引用本文:郭冬梅.基于状态压缩的最长公共上升子序列快速算法[J].计算机技术与发展,2014(5):40-43.
作者姓名:郭冬梅
作者单位:安徽理工大学计算机科学与工程学院,安徽淮南232001
基金项目:基金项目:安徽省高等学校省级优秀青年人才基金项目(2011SQRL040);安徽理工大学青年教师科学研究基金(2012QNY31)
摘    要:探讨了最长公共上升子序列(LCIS)问题,在前人算法的基础上提出一种高效求解LCIS的动态规划算法。对于LCIS问题,分别使用最长公共子序列(LCS)和最长上升子序列(LIS)相结合的算法、动态规划算法、经过状态压缩的改进动态规划算法进行设计,并对后两种算法进行了实现。设计的状态压缩的动态规划算法,实现了LCIS的快速求解。通过分析这三种算法的时间和空间复杂度,最终提出了时间复杂度为O(mn)、空间复杂度为O(m)或O(n)的基于状态压缩的快速LCIS算法。

关 键 词:最长公共上升子序列  最长公共子序列  最长上升子序列  动态规划  状态压缩

A Longest Common Increasing Subsequence Algorithm Based on State Compression
GUO Dong-mei.A Longest Common Increasing Subsequence Algorithm Based on State Compression[J].Computer Technology and Development,2014(5):40-43.
Authors:GUO Dong-mei
Affiliation:GUO Dong-mei ( College of Computer Science and Engineering, Anhui University of Science and Technology, Huainan 232001, China)
Abstract:Discussed the problem of a Longest Common Increasing Subsequence ( LCIS) ,put forword a fast dynamic algorithm for LCIS. For the LCIS problem,used respectively the algorithm of a Longest Common Subsequence ( LCS) combined a Longest Increasing Subse-quence (LIS) algorithm,dynamic programming algorithm,improved dynamic programming algorithm through state to design,and per-formed the second and the third algorithm. The designed state compressed dynamic programming algorithm realized a fast solution for LCIS. According to analyze the time and space complexity of the three algorithms,presented a fast algorithm for delivering a longest com-mon increasing subsequence in O( mn) time and O( m) or O( n) space finally.
Keywords:LCIS  LCS  LIS  dynamic programming  state compression
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