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文档讲解:代码随想录. 最长公共子序列
视频讲解:动态规划子序列问题经典题目 | LeetCode:1143.最长公共子序列
状态:已完成
代码实现
class Solution { public: int longestCommonSubsequence(string text1, string text2) { vector<vector<int>> dp(text1.size() + 1, vector<int>(text2.size() + 1, 0)); for (int i = 1; i <= text1.size(); i++) { for (int j = 1; j <= text2.size(); j++) { if (text1[i - 1] == text2[j - 1]) { dp[i][j] = dp[i - 1][j - 1] + 1; } else { dp[i][j] = max(dp[i - 1][j], dp[i][j-1]); } } } return dp[text1.size()][text2.size()]; } };
文档讲解:代码随想录.不相交的线
视频讲解:动态规划之子序列问题,换汤不换药 | LeetCode:1035.不相交的线
状态:已完成
class Solution { public: int maxUncrossedLines(vector<int>& A, vector<int>& B) { vector<vector<int>> dp(A.size() + 1, vector<int>(B.size() + 1, 0)); for (int i = 1; i <= A.size(); i++) { for (int j = 1; j <= B.size(); j++) { if (A[i - 1] == B[j - 1]) { dp[i][j] = dp[i - 1][j - 1] + 1; } else { dp[i][j] = max(dp[i - 1][j], dp[i][j - 1]); } } } return dp[A.size()][B.size()]; } };
文档讲解:代码随想录.最大子序和
视频讲解:看起来复杂,其实是简单动态规划 | LeetCode:53.最大子序和
状态:已完成
class Solution { public: int maxSubArray(vector<int>& nums) { if (nums.size() ==0) return 0; vector<int> dp(nums.size()); dp[0]=nums[0]; int result = dp[0]; for (int i = 1; i < nums.size(); i++) { dp[i] = max(dp[i - 1] + nums[i], nums[i]); if (dp[i] > result) result = dp[i]; } return result; } };
文档讲解:代码随想录.判断子序列
视频讲解:动态规划,用相似思路解决复杂问题 | LeetCode:392.判断子序列
状态:已完成
class Solution {
public:
bool isSubsequence(string s, string t) {
vector<vector<int>> dp(s.size() + 1, vector<int>(t.size() + 1, 0));
for (int i = 1; i <= s.size(); i++) {
for (int j = 1; j <= t.size(); j++) {
if (s[i - 1] == t[j - 1]) dp[i][j] = dp[i - 1][j - 1] + 1;
else dp[i][j] = dp[i][j - 1];
}
}
if (dp[s.size()][t.size()] == s.size()) return true;
return false;
}
};
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