搜索资源列表
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动态规划解决LCS-dynamic programming solution LCS
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动态规划实现lcs-Dynamic programming to achieve lcs
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用LCS方法解决字符匹配问题，用到动态规划的思想。原创-LCS solution with matching characters, the idea of using dynamic programming
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一道经典的动态规划题目
浙江大学硕士生入学复试上机题
http://acm.hdu.edu.cn/showproblem.php?pid=1231-Classic dynamic programming
http://acm.hdu.edu.cn/showproblem.php?pid=1231
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算法动态规划最长公共子序列的递归实现，并包括查找过程的体现-Dynamic programming algorithm for the longest common subsequence of the recursive implementation, and includes the process to find a manifestation of
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利用动态规划技术和递推的办法，求出两个字母表A和B的最大公共字串长度。-The use of dynamic programming techniques and recursive approach to find the two alphabets A and B, the largest public string length.
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算法设计与分析课程中用动态规划算法求解最长公共子序列问题，C语言写的，很实用，有b数组和c数组的输出，很适合初学者一步一步走程序。-Algorithm design and analysis programs using dynamic programming algorithm for solving the longest common subsequence problem, C language written, very practical, with b and c array ar
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LCS问题具有最优子结构和重叠子问题的性质，因此采用动态规划算法自底向上计算该问题的解，并输出求到的LCS。-LCS problem with sub-optimal substructure and overlapping nature of the problem, so a bottom-up dynamic programming algorithm for computing the solution of the problem, and the output request to
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算法导论中最长公共子序列的实现，采用动态规划方法-Introduction to Algorithms in the realization of the longest common subsequence, dynamic programming method
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利用动态规划算法寻找两个list中的最长公共子序列，并分别记录了最长公共子序列的在list中的结束位置-Dynamic programming algorithm to find the two list the longest common subsequence, and recorded the longest common subsequence of the end position in the list
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VC实现输入两个字符串，利用动态规划思想求的最长公共子序列。有可视化界面。-VC the input two strings, the use of dynamic programming requirements of the longest common subsequence. A visual interface.
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最长公共子序列的算法实现。基于动态规划的丝线实现的算法-The longest common subsequence algorithm. Realization of the algorithm based on dynamic programming thread
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实现最长公共子序列，使用动态规划算法，求两个序列的公共部分主要使用PHP-The public part of the longest common subsequence, using a dynamic programming algorithm, find two sequences using PHP
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HDOJ 1080 动态规划题目。欢迎各种讨论交流。-The dynamic programming topics HDOJ 1080. Welcome discussions AC.
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动态规划 最长子字符串匹配 可以输出多个匹配的子字符串 算法导论-Dynamic programming longest substring matching substring can output multiple matches Introduction to Algorithms
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根据X和Y序列，利用动态规划计算出的所有LCS-The X and Y sequences is calculated using dynamic programming all LCS
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求最长公共子序列。本算法使用动态规划算法，解得最长公共子序列问题。-Find the longest common subsequence. The algorithm uses a dynamic programming algorithm, the solution was the longest common subsequence problem.
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该程序用于求两个序列的最长子段，通过动态规划算法，记录子问题的结果，进而求出最终的最长子段。-The procedure used to find the longest sequence of two sub-sections, through dynamic programming algorithm to record the results of sub-problems, and then find the longest sub-section final.
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用python实现了最长公共子序列LCS代码，分别应用递归方法和动态规划实现。并且实现了三个字符串的最长公共子序列。-Using Python to achieve the longest common subsequence of LCS code, respectively using recursive method and dynamic programming. And the realization of the longest common subsequence of three
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大数据应用中基于支配点的mlcss算法设计与实现，程序中设计了三条字符串，查找他们之间的最长公共子序列。相对于传统的动态规划法，基于支配点思想具有更加高效的效率。(The design and implementation of mlcss algorithm based on dominant point in large data application, three strings are designed in the program to find the longest common
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