Longest Increasing Subsequence 最长递增子序列

子序列不是数组中连续的数。

dp表达的意思是以i结尾的最长子序列,而不是前i个数字的最长子序列。

初始化是dp所有的都为1,最终的结果是求dp所有的数值的最大值。

class Solution {
public:
int lengthOfLIS(vector<int>& nums) {
int length = nums.size();
if(length <= )
return ;
vector<int> dp(length,);
int max_num;
for(int i = ;i < length;i++){
max_num = ;
for(int j = i - ;j >= ;j--){
if(nums[i] > nums[j])
max_num = max(max_num,dp[j] + );
}
dp[i] = max_num;
}
max_num = ;
for(int i = ;i < length;i++){
if(dp[i] > max_num)
max_num = dp[i];
}
return max_num;
}
};

674. Longest Continuous Increasing Subsequence

相对于最长递增子序列来说,这个题目更加简单,只需要比较前一个数字就好,不用把前面的数字都比较完。因为如果比前一个小,直接就无法完成递增,只能保持当前的值1;如果比前一个数字大,其实前一个数字就已经计算了之前递增的个数,直接加1就好了

class Solution {
public:
int findLengthOfLCIS(vector<int>& nums) {
if(nums.empty())
return ;
int length = nums.size();
vector<int> dp(length,);
for(int i = ;i < length;i++){
if(nums[i] > nums[i-])
dp[i] = dp[i-] + ;
}
int max_num = ;
for(int i = ;i < length;i++)
max_num = max(max_num,dp[i]);
return max_num;
}
};

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