[LeetCode] 673. Number of Longest Increasing Subsequence 最长递增序列的个数

 

Given an unsorted array of integers, find the number of longest increasing subsequence.

Example 1:

Input: [1,3,5,4,7]
Output: 2
Explanation: The two longest increasing subsequence are [1, 3, 4, 7] and [1, 3, 5, 7].

 

Example 2:

Input: [2,2,2,2,2]
Output: 5
Explanation: The length of longest continuous increasing subsequence is 1, and there are 5 subsequences' length is 1, so output 5.

 

Note: Length of the given array will be not exceed 2000 and the answer is guaranteed to be fit in 32-bit signed int.

 

这道题给了我们一个数组,让求最长递增序列的个数,题目中的两个例子也很好的说明了问题。那么对于这种求极值的问题,直觉告诉我们应该要使用动态规划 Dynamic Programming 来做。其实这道题在设计 DP 数组的时候有个坑,如果将 dp[i] 定义为到i位置的最长子序列的个数的话,则递推公式不好找。但是如果将 dp[i] 定义为以 nums[i] 为结尾的递推序列的个数的话,再配上这些递推序列的长度,将会比较容易的发现递推关系。这里用 len[i] 表示以 nums[i] 为结尾的递推序列的长度,用 cnt[i] 表示以 nums[i] 为结尾的递推序列的个数,初始化都赋值为1,只要有数字,那么至少都是1。然后遍历数组,对于每个遍历到的数字 nums[i],再遍历其之前的所有数字 nums[j],当 nums[i] 小于等于 nums[j] 时,不做任何处理,因为不是递增序列。反之,则判断 len[i] 和 len[j] 的关系,如果 len[i] 等于 len[j] + 1,说明 nums[i] 这个数字可以加在以 nums[j] 结尾的递增序列后面,并且以 nums[j] 结尾的递增序列个数可以直接加到以 nums[i] 结尾的递增序列个数上。如果 len[i] 小于 len[j] + 1,说明找到了一条长度更长的递增序列,那么此时将 len[i] 更新为 len[j]+1,并且原本的递增序列都不能用了,直接用 cnt[j] 来代替。在更新完 len[i] 和 cnt[i] 之后,要更新 mx 和结果 res,如果 mx 等于 len[i],则把 cnt[i] 加到结果 res 之上;如果 mx 小于 len[i],则更新 mx 为 len[i],更新结果 res 为 cnt[i],参见代码如下:

 

解法一:

class Solution {
public:
    int findNumberOfLIS(vector<int>& nums) {
        int res = 0, mx = 0, n = nums.size();
        vector<int> len(n, 1), cnt(n, 1);
        for (int i = 0; i < n; ++i) {
            for (int j = 0; j < i; ++j) {
                if (nums[i] <= nums[j]) continue;
                if (len[i] == len[j] + 1) cnt[i] += cnt[j];
                else if (len[i] < len[j] + 1) {
                    len[i] = len[j] + 1;
                    cnt[i] = cnt[j];
                }
            }
            if (mx == len[i]) res += cnt[i];
            else if (mx < len[i]) {
                mx = len[i];
                res = cnt[i];
            }
        }
        return res;
    }
};

 

下面这种方法跟上面的解法基本一样,就是把更新结果 res 放在了遍历完数组之后,我们利用 mx 来找到所有的 cnt[i],累加到结果 res 上,参见代码如下:

 

解法二:

class Solution {
public:
    int findNumberOfLIS(vector<int>& nums) {
        int res = 0, mx = 0, n = nums.size();
        vector<int> len(n, 1), cnt(n, 1);
        for (int i = 0; i < n; ++i) {
            for (int j = 0; j < i; ++j) {
                if (nums[i] <= nums[j]) continue;
                if (len[i] == len[j] + 1) cnt[i] += cnt[j];
                else if (len[i] < len[j] + 1) {
                    len[i] = len[j] + 1;
                    cnt[i] = cnt[j];
                }
            }
            mx = max(mx, len[i]);
        }
        for (int i = 0; i < n; ++i) {
            if (mx == len[i]) res += cnt[i];
        }
        return res;
    }
};

 

Github 同步地址:

https://github.com/grandyang/leetcode/issues/673

 

类似题目:

Longest Increasing Subsequence

Longest Continuous Increasing Subsequence

 

参考资料:

https://leetcode.com/problems/number-of-longest-increasing-subsequence/

https://leetcode.com/problems/number-of-longest-increasing-subsequence/discuss/107318/C%2B%2B-DP-with-explanation-O(n2)

https://leetcode.com/problems/number-of-longest-increasing-subsequence/discuss/107293/JavaC%2B%2B-Simple-dp-solution-with-explanation

 

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posted @ 2017-09-27 21:06  Grandyang  阅读(10437)  评论(3编辑  收藏  举报
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