1: class Solution {
2: public:
3: int wiggleMaxLength(vector<int>& nums) {
4: if (nums.size() < 2) return nums.size();
5: vector<int> large(nums.size(), 1);
6: vector<int> small(nums.size(), 1);
7: for (int i = 1; i < nums.size(); i++) {
8: for (int j = i-1; j >= 0; j--) {
9: if (nums[i] > nums[j]) large[i] = max(large[i], small[j]+1);
10: else if (nums[i] < nums[j]) small[i] = max(small[i], large[j]+1);
11: }
12: }
13: return max(small[nums.size()-1], large[nums.size()-1]);
14: }
15: };
Tuesday, August 16, 2016
376. Wiggle Subsequence
I was trapped in finding a DP solution that dp[i] means the longest wiggle subsequence so far at index i. However, I then realized two things: 1. The wiggle subsequence is not necessary to be consecutive; 2. [2,1] is a wiggle and [1,2] is a wiggle too. So I can’t solve it by something like Kadane’s algorithm. I followed the top rated solution which uses two dp arrays and runs at O(n^2) because subsequence is not required to be consecutive.
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