斐波那契数列公式
斐波那契数列:
f ( n ) = n , n ⩽ 1 f(n)= n,n\leqslant 1f(n)=n,n⩽1
f ( n ) = f ( n − 1 ) + f ( n − 2 ) , n ≥ 2 f(n)=f(n-1)+f(n-2),n\geq 2f(n)=f(n−1)+f(n−2),n≥2
常用的迭代编程算法
#include <stdio.h>
#include <stdlib.h>
unsigned long fibo(unsigned long int n)
{
if(n <= 1)
return n;
else
return fibo(n-1) + fibo(n-2);
}
int main(int argc,char *argv[])
{
if(1 >= argc)
{
printf("usage:./fibo num");
return -1;
}
unsigned long n = atoi(argv[1]);
unsigned long fiboNum = fibo(n);
printf("the %lu result is %lu",n,fiboNum);
return 0;
}
以计算F(5)为例进行递归分析:
F(2) F(1)
F(3) F(0)
F(1)
F(4)
F(2) F(1)
F(0)
F(5)
F(2) F(1)
F(3) F(0)
F(1)
可以观察出F(1)被计算五次 等等。时间复杂度很大。
其次可能会导致栈溢出。(默认栈空间大小为8M)
递归改进版
#include <stdio.h>
#include <stdlib.h>
/*求斐波那契数列,避免重复计算版本*/
unsigned long fiboProcess(unsigned long *array,unsigned long n)
{
if(n < 2)
return n;
else
{
/*递归保存值*/
array[n] = fiboProcess(array,n-1) + array[n-2];
return array[n];
}
}
unsigned long fibo(unsigned long n)
{
if(n <= 1)
return n;
unsigned long ret = 0;
/*申请数组用于保存已经计算过的内容*/
unsigned long *array = (unsigned long*)calloc(n+1,sizeof(unsigned long));
if(NULL == array)
{
return -1;
}
array[1] = 1;
ret = fiboProcess(array,n);
free(array);
array = NULL;
return ret;
}
int main(int argc,char *argv[])
{
if(1 >= argc)
{
printf("usage:./fibo num");
return -1;
}
unsigned long n = atoi(argv[1]);
unsigned long fiboNum = fibo(n);
printf("the %lu result is %lu",n,fiboNum);
return 0;
}
时间复杂度为O(n)。
迭代解法
#include <stdio.h>
#include <stdlib.h>
/*求斐波那契数列迭代版*/
unsigned long fibo(unsigned long n)
{
unsigned long preVal = 1;
unsigned long prePreVal = 0;
if(n <= 2)
return n;
unsigned long loop = 1;
unsigned long returnVal = 0;
while(loop < n)
{
returnVal = preVal +prePreVal;
/*更新记录结果*/
prePreVal = preVal;
preVal = returnVal;
loop++;
}
return returnVal;
}
int main(int argc,char *argv[])
{
if(1 >= argc)
{
printf("usage:./fibo num");
return -1;
}
unsigned long n = atoi(argv[1]);
unsigned long fiboNum = fibo(n);
printf("the %lu result is %lu",n,fiboNum);
return 0;
}
时间复杂度为O(n)
尾递归解法
#include <stdio.h>
#include <stdlib.h>
/*求斐波那契数列尾递归版*/
unsigned long fiboProcess(unsigned long n,unsigned long prePreVal,unsigned long preVal,unsigned long begin)
{
/*如果已经计算到我们需要计算的,则返回*/
if(n == begin)
return preVal+prePreVal;
else
{
begin++;
return fiboProcess(n,preVal,prePreVal+preVal,begin);
}
}
unsigned long fibo(unsigned long n)
{
if(n <= 1)
return n;
else
return fiboProcess(n,0,1,2);
}
int main(int argc,char *argv[])
{
if(1 >= argc)
{
printf("usage:./fibo num");
return -1;
}
unsigned long n = atoi(argv[1]);
unsigned long fiboNum = fibo(n);
printf("the %lu result is %lu",n,fiboNum);
return 0;
}
尾递归在函数返回之前的最后一个操作仍然是递归调用。尾递归的好处是,进入下一个函数之前,已经获得了当前函数的结果,因此不需要保留当前函数的环境,内存占用自然也是比最开始提到的递归要小。时间复杂度为O(n)。
矩阵快速幂解法
推导如下:
假设有2*2的矩阵A满足下面的等式:
A ∗ [ f ( n − 1 ) f ( n − 2 ) ] = [ f ( n ) f ( n − 1 ) ] = [ f ( n − 1 ) + f ( n − 2 ) f ( n − 1 ) ] A* \begin{bmatrix} f(n-1)\\ f(n-2) \end{bmatrix} =\begin{bmatrix} f(n)\\ f(n-1) \end{bmatrix}= \begin{bmatrix} f(n-1)+f(n-2)\\ f(n-1) \end{bmatrix}A∗[f(n−1)f(n−2)]=[f(n)f(n−1)]=[f(n−1)+f(n−2)f(n−1)]
可以得到矩阵A
[ 1 1 1 0 ] \begin{bmatrix} 1 & 1\\ 1 & 0 \end{bmatrix}[1110]
即可以得到下面的矩阵等式
[ 1 1 1 0 ] ∗ [ f ( n − 1 ) f ( n − 2 ) ] = [ f ( n ) f ( n − 1 ) ] \begin{bmatrix} 1 & 1\\ 1 & 0 \end{bmatrix}*\begin{bmatrix} f(n-1)\\ f(n-2) \end{bmatrix}=\begin{bmatrix} f(n)\\ f(n-1) \end{bmatrix}[1110]∗[f(n−1)f(n−2)]=[f(n)f(n−1)]
再进行变换:
[ 1 1 1 0 ] ∗ [ 1 1 1 0 ] ∗ [ f ( n − 2 ) f ( n − 3 ) ] = [ f ( n ) f ( n − 1 ) ] \begin{bmatrix} 1 & 1\\ 1 & 0 \end{bmatrix}*\begin{bmatrix} 1 & 1\\ 1 & 0 \end{bmatrix}*\begin{bmatrix} f(n-2)\\ f(n-3) \end{bmatrix}=\begin{bmatrix} f(n)\\ f(n-1) \end{bmatrix}[1110]∗[1110]∗[f(n−2)f(n−3)]=[f(n)f(n−1)]
即
[ 1 1 1 0 ] n − 1 ∗ [ f ( 1 ) f ( 0 ) ] = [ f ( n ) f ( n − 1 ) ] \begin{bmatrix} 1 & 1\\ 1 & 0 \end{bmatrix}^{n-1}*\begin{bmatrix} f(1)\\ f(0) \end{bmatrix}=\begin{bmatrix} f(n)\\ f(n-1) \end{bmatrix}[1110]n−1∗[f(1)f(0)]=[f(n)f(n−1)]
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#define MAX_COL 2
#define MAX_ROW 2
typedef unsigned long MatrixType;
/*计算2*2矩阵乘法,这里没有写成通用形式,有兴趣的可以自己实现通用矩阵乘法*/
int matrixDot(MatrixType A[MAX_ROW][MAX_COL],MatrixType B[MAX_ROW][MAX_COL],MatrixType C[MAX_ROW][MAX_COL])
{
/*C为返回结果,由于A可能和C相同,因此使用临时矩阵存储*/
MatrixType tempMa[MAX_ROW][MAX_COL] ;
memset(tempMa,0,sizeof(tempMa));
/*这里简便处理*/
tempMa[0][0] = A[0][0] * B[0][0] + A[0][1] * B [1][0];
tempMa[0][1] = A[0][0] * B[0][1] + A[0][1] * B [1][1];
tempMa[1][0] = A[1][0] * B[0][0] + A[1][1] * B [1][0];
tempMa[1][1] = A[1][0] * B[0][1] + A[1][1] * B [1][1];
memcpy(C,tempMa,sizeof(tempMa));
return 0;
}
MatrixType fibo(int n)
{
if(n <= 1)
return n;
MatrixType result[][MAX_COL] = {1,0,0,1};
MatrixType A[][2] = {1,1,1,0};
while (n > 0)
{
/*判断最后一位是否为1,即可知奇偶*/
if (n&1)
{
matrixDot(result,A,result);
}
n /= 2;
matrixDot(A,A,A);
}
return result[0][1];
}
int main(int argc,char *argv[])
{
if(1 >= argc)
{
printf("usage:./fibo num");
return -1;
}
unsigned long n = atoi(argv[1]);
unsigned long fiboNum = fibo(n);
printf("the %lu result is %lu",n,fiboNum);
return 0;
}
可以看到,计算次数类似与二分查找次数,其时间复杂度为O(logn)
通项公式解法
通项公式为:
f ( n ) = ( 1 + 5 2 ) n − ( 1 − 5 2 ) n 5 f(n)= \frac{(\frac{1+\sqrt{5}}{2})^{n}-(\frac{1-\sqrt{5}}{2})^{n}}{\sqrt{5}}f(n)=5(21+5)n−(21−5)n
#include <stdio.h>
#include <stdlib.h>
#include <math.h>
unsigned long fibo(unsigned long n)
{
if(n <=1 )
return n;
return (unsigned long)((pow((1+sqrt(5))/2,n)-pow((1-sqrt(5))/2,n))/sqrt(5));
}
int main(int argc,char *argv[])
{
if(1 >= argc)
{
printf("usage:./fibo num");
return -1;
}
unsigned long n = atoi(argv[1]);
unsigned long fiboNum = fibo(n);
printf("the %lu result is %lu",n,fiboNum);
return 0;
}
列表法
如果需要求解的斐波那契数列的第n个在有限范围内,那么完全可以将已知的斐波那契数列存储起来,在需要的时候读取即可,时间复杂度可以为O(1)。