Longest Palindromic Substring & Longest Palindromic Subsequence

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5. Longest Palindromic Substring

题目链接:https://leetcode.com/problems/longest-palindromic-substring/#/description

题目大意:给定一个字符串s,返回该字符串的最长回文子串。s的最大长度不超过1000.

 

思路:对于每个子串的中心(可以是一个字符,或者是两个字符的间隙,比如串abc,中心可以是a,b,c,或者是ab的间隙,bc的间隙)往两边同时进行扫描,直到不是回文串为止。假设字符串的长度为n,那么中心的个数为2*n-1(字符作为中心有n个,间隙有n-1个)。

算法复杂度:对于每个中心往两边扫描的复杂度为O(n),所以时间复杂度为O(n^2),空间复杂度为O(1)

代码:

 1 class Solution {
 2 public:
 3     string longestPalindrome(string s) {
 4         if (s == "")
 5             return s;
 6         int start = 0, maxLen = 1;
 7         for (int i = 1; i < s.size(); ++i) {
 8             expandStr(s, i - 1, i, start, maxLen);
 9             expandStr(s, i - 1, i + 1, start, maxLen);
10         }
11         return s.substr(start, maxLen);
12     }
13 private:
14     void expandStr(string &s, int low, int high, int &start, int &maxLen) {
15         while (low >= 0 && high < s.size() && s[low] == s[high]) {
16             --low;
17             ++high;
18         }
19         if (high - low - 1 > maxLen) {
20             start = low + 1;
21             maxLen = high - low - 1;
22         }
23     }
24 };

评测系统上运行结果:

技术分享

 

516. Longest Palindromic Subsequence

题目链接:https://leetcode.com/problems/longest-palindromic-subsequence/#/description

题目大意:给定一个字符串s,返回该字符串的最长回文子序列。s的最大长度不超过1000.

 

思路:使用动态规划。longest数组记录字符串[i,j]范围的最长回文序列,动态转移方程为longest[l][r] = longest[l+1][r-1] + 2 if s[l] == s[r] else longest[l][r] = max(longest[l+1][r], longest[l][r-1]).

算法复杂度:时间复杂度为O(n^2),空间复杂度为O(n^2)

代码:

 1 class Solution {
 2 public:
 3     int longestPalindromeSubseq(string s) {
 4         if (s.empty())
 5             return 0;
 6         vector<vector<int>> longest(s.size(), vector<int>(s.size()));
 7         for (int len = 1; len <= s.size(); ++len)
 8             for (int l = 0; l + len <= s.size(); ++l) {
 9                 int r = l + len - 1;
10                 if (l == r)
11                     longest[l][r] = 1;
12                 else if (s[l] == s[r])
13                     longest[l][r] = longest[l+1][r-1] + 2;
14                 else
15                     longest[l][r] = max(longest[l+1][r], longest[l][r-1]);
16             }
17         return longest[0][s.size() - 1];
18     }
19 };

评测系统上运行结果:

技术分享

 

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