动态规划解题步骤(重要):
- 确定dp数组(dp table)以及下标的含义
- 确定递推公式
- dp数组如何初始化
- 确定遍历顺序
- 举例推导dp数组
509. 斐波那契数
class Solution {
public:
// 时间复杂度:O(n)
// 空间复杂度:O(n)
int fibDp1(int n) {
if (n <= 1) {
return n;
}
vector<int> dp(n + 1);
dp[0] = 0;
dp[1] = 1;
for (int i = 2; i <= n; i++) {
dp[i] = dp[i - 1] + dp[i - 2];
}
return dp[n];
}
// 时间复杂度:O(n)
// 空间复杂度:O(1)
int fibDp2(int n) {
if (n <= 1) {
return n;
}
int dp[2];
dp[0] = 0;
dp[1] = 1;
for (int i = 2; i <= n; i++) {
int sum = dp[0] + dp[1];
dp[0] = dp[1];
dp[1] = sum;
}
return dp[1];
}
// 递归
// 时间复杂度:O(2^n)
// 空间复杂度:O(n),算上了编程语言中实现递归的系统栈所占空间
int fibTraversal(int n) {
if (n < 2) {
return n;
}
return fibTraversal(n - 1) + fibTraversal(n - 2);
}
int fib(int n) {
return 0;
}
};
70. 爬楼梯
class Solution {
public:
int climbStairs(int n) {
if (n <= 1) {
return n;
}
vector<int> dp(n + 1);
dp[1] = 1;
dp[2] = 2;
for (int i = 3; i <= n; i++) {
dp[i] = dp[i - 1] + dp[i - 2];
}
return dp[n];
}
int climbStairs1(int n) {
if (n <= 1) {
return n;
}
int dp[3];
dp[1] = 1;
dp[2] = 2;
for (int i = 3; i <= n; i++) {
int sum = dp[1] + dp[2];
dp[1] = dp[2];
dp[2] = sum;
}
return dp[2];
}
// 通用版,一步m个台阶,爬n个台阶
int _climbStairs(int n, int m) {
vector<int> dp(n + 1, 0);
dp[0] = 1;
for (int i = 1; i <= n; i++) {
for (int j = 1; j <= m; j++) {
if (i - j >= 0) {
dp[i] += dp[i - j];
}
}
}
return dp[n];
}
};
746. 使用最小花费爬楼梯
class Solution {
public:
int minCostClimbingStairs(vector<int>& cost) {
vector<int> dp(cost.size() + 1);
dp[0] = 0;
dp[1] = 0;
for (int i = 2; i <= cost.size(); ++i) {
dp[i] = min(dp[i - 1] + cost[i - 1], dp[i - 2] + cost[i - 2]);
}
return dp[cost.size()];
}
int minCostClimbingStairs1(vector<int>& cost) {
int dp[2];
dp[0] = 0;
dp[1] = 0;
for (int i = 2; i <= cost.size(); ++i) {
int dpi = min(dp[0] + cost[i - 2], dp[1] + cost[i - 1]);
dp[0] = dp[1];
dp[1] = dpi;
}
return dp[1];
}
};