poj 3734 Blocks(矩阵快速幂)

本文探讨了一个有趣的数学问题:如何计算在特定条件下(红色和绿色方块数量必须为偶数),用四种颜色对一排方块进行涂色的不同方式的数量。通过动态规划方法转化为矩阵运算,并利用快速幂求解。

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Blocks
Time Limit: 1000MS Memory Limit: 65536K
Total Submissions: 6472 Accepted: 3117

Description

Panda has received an assignment of painting a line of blocks. Since Panda is such an intelligent boy, he starts to think of a math problem of painting. Suppose there are N blocks in a line and each block can be paint red, blue, green or yellow. For some myterious reasons, Panda want both the number of red blocks and green blocks to be even numbers. Under such conditions, Panda wants to know the number of different ways to paint these blocks.

Input

The first line of the input contains an integer T(1≤T≤100), the number of test cases. Each of the next T lines contains an integer N(1≤N≤10^9) indicating the number of blocks.

Output

For each test cases, output the number of ways to paint the blocks in a single line. Since the answer may be quite large, you have to module it by 10007.

Sample Input

2
1
2

Sample Output

2
6

Source


题解:这道题第一感觉是dp,然后仔细考虑考虑到第i个方块,设同时为偶数的方案数为ai,有一个为偶数的方案数为bi,全是奇数的方案数是ci

a(i+1)=2*ai+bi

,b(i+1)=2*ai+2*bi+2*ci;

c(i+1)=bi+2*ci;

然后可以得到矩阵,之后求快速幂就行了


代码

#include <vector>
#include <cstdio>
#include <iostream>
//#include <bits/stdc++.h>

using namespace std;
const int M=10007;  //修改余数
typedef vector<int>  vec;
typedef vector<vec>  mat;
typedef long long LL;
mat mul(mat &A,mat &B)
{
    mat C(A.size(),vec(B[0].size()));
    for(int i=0;i<A.size();i++)
    {
        for(int k=0;k<B.size();k++)
        {
            for(int j=0;j<B[0].size();j++)
                    C[i][j]=(C[i][j]+A[i][k]*B[k][j])%M;
        }
    }
    return C;
}

mat pow(mat A,LL n)
{
    mat B(A.size(),vec(A.size()));
    for(int i=0;i<A.size();i++)
        B[i][i]=1;
    while(n>0)
    {
        if(n&1) B=mul(B,A);
        A=mul(A,A);
        n>>=1;
    }
    return B;
}

LL n;
int main()
{
    int t;
    cin>>t;
    while(t--){
        cin>>n;
        mat A(3,vec(3));
        A[0][0]=A[1][1]=A[1][2]=A[1][0]=A[2][2]=2;
        A[0][1]=A[2][1]=1;
        A[2][0]=A[0][2]=0;
        //cout<<1<<endl;
        A=pow(A,n);
        cout<<A[0][0]<< endl;
    }
    return 0;
}


以下是Java解决POJ3233—矩阵幂序列问题的代码和解释: ```java import java.util.Scanner; public class Main { static int n, k, m; static int[][] A, E; public static void main(String[] args) { Scanner sc = new Scanner(System.in); n = sc.nextInt(); k = sc.nextInt(); m = sc.nextInt(); A = new int[n][n]; E = new int[n][n]; for (int i = 0; i < n; i++) { for (int j = 0; j < n; j++) { A[i][j] = sc.nextInt() % m; E[i][j] = (i == j) ? 1 : 0; } } int[][] res = matrixPow(A, k); int[][] ans = matrixAdd(res, E); printMatrix(ans); } // 矩阵乘法 public static int[][] matrixMul(int[][] a, int[][] b) { int[][] c = new int[n][n]; for (int i = 0; i < n; i++) { for (int j = 0; j < n; j++) { for (int k = 0; k < n; k++) { c[i][j] = (c[i][j] + a[i][k] * b[k][j]) % m; } } } return c; } // 矩阵快速幂 public static int[][] matrixPow(int[][] a, int b) { int[][] res = E; while (b > 0) { if ((b & 1) == 1) { res = matrixMul(res, a); } a = matrixMul(a, a); b >>= 1; } return res; } // 矩阵加法 public static int[][] matrixAdd(int[][] a, int[][] b) { int[][] c = new int[n][n]; for (int i = 0; i < n; i++) { for (int j = 0; j < n; j++) { c[i][j] = (a[i][j] + b[i][j]) % m; } } return c; } // 输出矩阵 public static void printMatrix(int[][] a) { for (int i = 0; i < n; i++) { for (int j = 0; j < n; j++) { System.out.print(a[i][j] + " "); } System.out.println(); } } } ``` 解释: 1. 首先读入输入的n、k、m和矩阵A,同时初始化单位矩阵E。 2. 然后调用matrixPow函数求出A的k次幂矩阵res。 3. 最后将res和E相加得到结果ans,并输出。 4. matrixMul函数实现矩阵乘法,matrixPow函数实现矩阵快速幂,matrixAdd函数实现矩阵加法,printMatrix函数实现输出矩阵
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