解法2:题中让用divide and conquer的方法来做。 Java: 1 2 3 4 5 6 7 8 9 10 publicclassSolution { publicintmaxSubArray(int[] nums) { intres = Integer.MIN_VALUE, curSum =0; for(intnum : nums) { curSum = Math.max(curSum + num
divide and conquer...') print("Maximum contiguous sum is",find_maximum_subarray(A, 0, len(A) - 1), '\n') print('using Kanade Algorithm...') print("Maximum contiguous sum is", maxSubArraySum(A, len(A)), '\n') print('using dynamic programming...') MS = DP_maximum_subarray(...
maxSubArray(A, i) = maxSubArray(A, i - 1) >0 ? maxSubArray(A, i - 1) :0 + A[i]; 即得到了n个数的数列与n-1个数的数列的关系,最开始我觉得似乎没有涵盖所有情况,但是后面推导发现所有情况都被这个式子给解决了,很神奇,但是给我自己思考,我确实没有找到思考出这个思想的切入点,实际上它这个...
Subarray AdditionThe Kadane's Algorithm and Divide and Conquer algorithm share a commonality in their utilization, which is the ability to compute the maximum sum of a subarray within an array and determine which subarray holds that maximum sum. To accomplish this, it requires time to traverse ...
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: classSolution{public:intmaxSubArray(vector<int>&nums){intlen=nums.size();if(len==1)returnnums[0];vector<int>dp(len,0);dp[0]=nums[0];intmax...
Ans: No, Kadane's algorithm is not a divide-and-conquer algorithm. Q5: Can Kadane's algorithm be used to solve the maximum subarray problem in two-dimensional arrays? Ans: No, Kadane's algorithm is only suitable for one-dimensional arrays. Q6: Can Kadane's algorithm be used to find the...
本文将介绍计算机算法中的经典问题——最大子数组问题(maximum subarray problem)。所谓的最大子数组问题,指的是:给定一个数组A,寻找A的和最大的非空连续...
本文将介绍计算机算法中的经典问题——最大子数组问题(maximum subarray problem)。所谓的最大子数组问题,指的是:给定一个数组A,寻找A的和最大的非空连续子数组。比如,数组 A = [-2, -3, 4, -1, -2, 1, 5, -3], 最大子数组应为[4, -1, -2, 1, 5],其和为7。 首先,如果...
the contiguous subarray [4,-1,2,1] has the largest sum = 6. Solution1 (Brute Force) class Solution { public: int maxSubArray(vector<int>& nums) { int MaxInWhole = nums.at(0); // the max value in all the arries; for (int i = 0; i < nums.size(); i++) { ...
the contiguous subarray[4,−1,2,1]has the largest sum =6. More practice: If you have figured out the O(n) solution, try coding another solution using the divide and conquer approach, which is more subtle. https://oj.leetcode.com/problems/maximum-subarray/ ...