LC 873. Length of Longest Fibonacci Subsequence
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A sequence X_1, X_2, ..., X_n
is fibonacci-like if:
n >= 3
X_i + X_{i+1} = X_{i+2}
for alli + 2 <= n
Given a strictly increasing array A
of positive integers forming a sequence, find the length of the longest fibonacci-like subsequence of A
. If one does not exist, return 0.
(Recall that a subsequence is derived from another sequence A
by deleting any number of elements (including none) from A
, without changing the order of the remaining elements. For example, [3, 5, 8]
is a subsequence of [3, 4, 5, 6, 7, 8]
.)
Example 1:
Input: [1,2,3,4,5,6,7,8] Output: 5 Explanation: The longest subsequence that is fibonacci-like: [1,2,3,5,8].
Example 2:
Input: [1,3,7,11,12,14,18] Output: 3 Explanation: The longest subsequence that is fibonacci-like: [1,11,12], [3,11,14] or [7,11,18].
Note:
3 <= A.length <= 1000
1 <= A[0] < A[1] < ... < A[A.length - 1] <= 10^9
- (The time limit has been reduced by 50% for submissions in Java, C, and C++.)
my solution.
Runtime: 935 ms, faster than 2.29% of Java online submissions for Length of Longest Fibonacci Subsequence.
我的思路,采用map,虽然也是dp,但是还是一个n2的时间复杂度,看了别人的做法,用的是头尾指针逼近,二分法。今天的周赛里判断数组成三角形的快速判断方法也是这样的。
class Solution { public int lenLongestFibSubseq(int[] A) { Map<Integer, Map<Integer,Integer>> mp = new HashMap<>(); int ret = 0; for(int i=0; i<A.length; i++){ if(i == 0) mp.put(A[i], new HashMap<>()); else { mp.put(A[i],new HashMap<>()); Map<Integer,Integer> mpai = mp.get(A[i]); for(int j=0; j<i; j++){ Map<Integer,Integer> mpaj = mp.get(A[j]); mpai.put(A[j], mpaj.getOrDefault(A[i]-A[j],0)+1); ret = Math.max(ret, mpai.get(A[j])); } } } return ret > 1 ? ret + 1 : 0; } }
网上的思路。
Runtime: 41 ms, faster than 94.29% of Java online submissions for Length of Longest Fibonacci Subsequence.
class Solution { public int lenLongestFibSubseq(int[] A) { if(A.length < 3) return 0; int ret = 0; int[][] dp = new int[A.length][A.length]; for(int i=2; i<A.length; i++){ int left = 0, right = i-1; while(left < right){ if(A[left] + A[right] == A[i]){ dp[right][i] = dp[left][right]+1; ret = Math.max(ret, dp[right][i]); left++; right--; }else if(A[left] + A[right] > A[i]){ right--; }else { left++; } } } return ret == 0 ? 0 : ret + 2; } }
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