53. Maximum Subarray

最新推荐文章于 2025-09-04 16:45:21 发布

转载最新推荐文章于 2025-09-04 16:45:21 发布 · 66 阅读

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原文链接：http://www.cnblogs.com/ruruozhenhao/p/9813721.html

文章标签：

#c/c++ #runtime

本文详细解析了求解最大子数组和问题的算法，通过动态规划方法实现了O(n)的时间复杂度，提供了完整的C++代码实现，并提及了后续可尝试的分治法解决方案。

Given an integer array nums, find the contiguous subarray (containing at least one number) which has the largest sum and return its sum.

Example:

Input: [-2,1,-3,4,-1,2,1,-5,4],
Output: 6
Explanation: [4,-1,2,1] has the largest sum = 6.

Follow up:

If you have figured out the O(n) solution, try coding another solution using the divide and conquer approach, which is more subtle.

AC code:

class Solution {
public:
    int maxSubArray(vector<int>& nums) {
        int len = nums.size();
        if (len == 1)
            return nums[0];
        vector<int> dp(len, 0);
        dp[0] = nums[0];
        int maxx = dp[0];
        for (int i = 1; i < len; ++i) {
            dp[i] = nums[i] + (dp[i-1] > 0? dp[i-1] : 0);
            maxx = max(maxx, dp[i]);
        }
        return maxx;
    }
};

Runtime: 4 ms, faster than 100.00% of C++ online submissions for Maximum Subarray

转载于:https://www.cnblogs.com/ruruozhenhao/p/9813721.html