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LeetCode:Distinct Subsequences

2013-11-24 14:50 363 查看
我的LeetCode解题报告索引

题目链接

Given a string S and a string T, count the number of distinct subsequences of T in S.

A subsequence of a string is a new string which is formed from the original string by deleting some (can be none) of the characters without disturbing the relative positions of the remaining characters. (ie,
"ACE"
is a subsequence of
"ABCDE"
while
"AEC"
is not).

Here is an example:
S =
"rabbbit"
, T =
"rabbit"


Return
3
.

题目大意:删除S中某些位置的字符可以得到T,总共有几种不同的删除方法

设S的长度为lens,T的长度为lent

算法1:递归解法,首先,从个字符串S的尾部开始扫描,找到第一个和T最后一个字符相同的位置k,那么有下面两种匹配:a. T的最后一个字符和S[k]匹配,b. T的最后一个字符不和S[k]匹配。a相当于子问题:从S[0...lens-2]中删除几个字符得到T[0...lent-2],b相当于子问题:从S[0...lens-2]中删除几个字符得到T[0...lent-1]。那么总的删除方法等于a、b两种情况的删除方法的和。递归解法代码如下,但是通过大数据会超时:

class Solution {
public:
int numDistinct(string S, string T) {
// IMPORTANT: Please reset any member data you declared, as
// the same Solution instance will be reused for each test case.
return numDistanceRecur(S, S.length()-1, T, T.length()-1);
}
int numDistanceRecur(string &S, int send, string &T, int tend)
{
if(tend < 0)return 1;
else if(send < 0)return 0;
while(send >= 0 && S[send] != T[tend])send--;
if(send < 0)return 0;
return numDistanceRecur(S,send-1,T,tend-1) + numDistanceRecur(S,send-1,T,tend);
}
};


View Code
算法2:动态规划,设dp[i][j]是从字符串S[0...i]中删除几个字符得到字符串T[0...j]的不同的删除方法种类,有上面递归的分析可知,动态规划方程如下

如果S[i] = T[j], dp[i][j] = dp[i-1][j-1]+dp[i-1][j]

如果S[i] 不等于 T[j], dp[i][j] = dp[i-1][j]

初始条件:当T为空字符串时,从任意的S删除几个字符得到T的方法为1

代码如下: 本文地址

class Solution {
public:
int numDistinct(string S, string T) {
// IMPORTANT: Please reset any member data you declared, as
// the same Solution instance will be reused for each test case.
int lens = S.length(), lent = T.length();
if(lent == 0)return 1;
else if(lens == 0)return 0;
int dp[lens+1][lent+1];
memset(dp, 0 , sizeof(dp));
for(int i = 0; i <= lens; i++)dp[i][0] = 1;
for(int i = 1; i <= lens; i++)
{
for(int j = 1; j <= lent; j++)
{
if(S[i-1] == T[j-1])
dp[i][j] = dp[i-1][j-1]+dp[i-1][j];
else dp[i][j] = dp[i-1][j];
}
}
return dp[lens][lent];
}
};


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