5.Longest Palindromic Substring (String; DP, KMP)
Given a string S, find the longest palindromic substring in S. You may assume that the maximum length of S is 1000, and there exists one unique longest palindromic substring.
思路I:动态规划,遍历到i的时候要保证之前的元素都已经计算过状态,所以遍历顺序同插入排序,时间复杂度O(n2)
class Solution {
public:
string longestPalindrome(string s) {
int len = s.length();
if(len==) return s; bool dp[len][len]={false};
int maxLen=;
int start=; //initialize
for(int i = ; i < len; i++){
dp[i][i]=true;
} for(int i=; i<len; i++){
for(int j = ; j<i; j++){
if(s[i]==s[j] && (j==i- || dp[j+][i-])){
dp[j][i]=true;
if(i-j+ > maxLen){
maxLen=i-j+;
start=j;
}
}
}
} return s.substr(start, maxLen);
}
};
思路II:KMP,一种字符串匹配方法。
- If P[ i ] ≤ R – i, we set P[ i ] to P[ i' ] which takes exactly one step.
- Otherwise we attempt to change the palindrome’s center to i by expanding it starting at the right edge, R. Extending R (the inner while loop) takes at most a total of N steps, and positioning and testing each centers take a total of N steps too. Therefore, this algorithm guarantees to finish in at most 2*N steps, giving a linear time solution.
那么总共时间复杂度最坏是O(n2),最好是O(n)
class Solution {
public:
string preProcess(string s) {
int n = s.length();
if (n == ) return "^$";
string ret = "^"; //开始符^
for (int i = ; i < n; i++)
ret += "#" + s.substr(i, ); ret += "#$"; //结束符$
return ret;
} string longestPalindrome(string s) {
string T = preProcess(s);
int n = T.length();
int *P = new int[n]; //状态数组长度等于原来字符串的长度,不用给#计算状态
int C = , R = ;
for (int i = ; i < n-; i++) {
int i_mirror = *C-i; // equals to i_mirror = C - (i-C) //if p[i_mirror] < R-i: set p[i] to p[i_mirror]
P[i] = (R > i) ? min(R-i, P[i_mirror]) : ; //else: Attempt to expand palindrome centered at i
while (T[i + + P[i]] == T[i - - P[i]]) //因为有哨兵^$所以不用担心越界; +1, -1检查下一个元素是否相等,若相等,扩大p[i]
P[i]++; //if the palindrome centered at i does expand past R
if (i + P[i] > R) {
C = i;
R = i + P[i];
}
} // Find the maximum element in P.
int maxLen = ;
int centerIndex = ;
for (int i = ; i < n-; i++) {
if (P[i] > maxLen) {
maxLen = P[i];
centerIndex = i;
}
}
delete[] P; return s.substr((centerIndex - - maxLen)/, maxLen);
}
};
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