('using 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_...
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....
publicintmaxSubArray(int[] nums) { intres = Integer.MIN_VALUE, curSum =0; for(intnum : nums) { curSum = Math.max(curSum + num, num); res = Math.max(res, curSum); } returnres; } } Java: Divide and conquer 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 ...
If you have figured out the O(n) solution, try coding another solution using the divide and conquer approach, which is more subtle. 贪心算法,当连续和sum>0时,sum+=A[i],负责sum=A[i] classSolution {public:intmaxSubArray(intA[],intn) {intmax=A[0],sum=0;for(inti=0;i<n;++i) {if...
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. Hide Tags Divide and Conquer Array Dynamic Programming ...
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. 题目大意 给定一个整数数组 nums ,找到一个具有最大和的连续子数组(子数组最少包含一个元素),...
Given an integer array nums, find the contiguous subarray (containing at least one number) which has the largest sum and return its sum. 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. ...
Input:[-2,1,-3,4,-1,2,1,-5,4],Output:6Explanation:[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. ...
If you’re here, it’s because you were trying to solve the "Maximum Subarray Sum Problem" and came across Kadane’s Algorithm but couldn’t figure out how something like that works. Or maybe you were bored of using Kadane’s Algorithm as a "black box". Or perhaps you wanted to know...
If you have figured out the O( n ) solution, try coding another solution using the divide and conquer approach, which is more subtle. Solution Approach 1: o(n) currSum = max(nums[i], currSum+nums[i]) # The maximum value before the nums[i] ...