我已经实现了记忆所有计算权力的算法，然后在需要时使用它们。比如x^13等于(x^2)^2^2 * x^2 * x其中x^2^2是从表中取出来的而不是再计算一次。这基本上是@Pramod answer的实现(但在c#中)。 需要的乘法数是Ceil(Log n)

public static int Power(int base, int exp)
{
    int tab[] = new int[exp + 1];
    tab[0] = 1;
    tab[1] = base;
    return Power(base, exp, tab);
}

public static int Power(int base, int exp, int tab[])
    {
         if(exp == 0) return 1;
         if(exp == 1) return base;
         int i = 1;
         while(i < exp/2)
         {  
            if(tab[2 * i] <= 0)
                tab[2 * i] = tab[i] * tab[i];
            i = i << 1;
          }
    if(exp <=  i)
        return tab[i];
     else return tab[i] * Power(base, exp - i, tab);
}

O(log N)的解决方案在Swift…

// Time complexity is O(log N)
func power(_ base: Int, _ exp: Int) -> Int { 

    // 1. If the exponent is 1 then return the number (e.g a^1 == a)
    //Time complexity O(1)
    if exp == 1 { 
        return base
    }

    // 2. Calculate the value of the number raised to half of the exponent. This will be used to calculate the final answer by squaring the result (e.g a^2n == (a^n)^2 == a^n * a^n). The idea is that we can do half the amount of work by obtaining a^n and multiplying the result by itself to get a^2n
    //Time complexity O(log N)
    let tempVal = power(base, exp/2) 

    // 3. If the exponent was odd then decompose the result in such a way that it allows you to divide the exponent in two (e.g. a^(2n+1) == a^1 * a^2n == a^1 * a^n * a^n). If the eponent is even then the result must be the base raised to half the exponent squared (e.g. a^2n == a^n * a^n = (a^n)^2).
    //Time complexity O(1)
    return (exp % 2 == 1 ? base : 1) * tempVal * tempVal 

}

int pow( int base, int exponent)

{   // Does not work for negative exponents. (But that would be leaving the range of int) 
    if (exponent == 0) return 1;  // base case;
    int temp = pow(base, exponent/2);
    if (exponent % 2 == 0)
        return temp * temp; 
    else
        return (base * temp * temp);
}

如果要取2的a次方。最快的方法是按幂位移位。

2 ** 3 == 1 << 3 == 8
2 ** 30 == 1 << 30 == 1073741824 (A Gigabyte)

power()函数只适用于整数

int power(int base, unsigned int exp){

    if (exp == 0)
        return 1;
    int temp = power(base, exp/2);
    if (exp%2 == 0)
        return temp*temp;
    else
        return base*temp*temp;

}

复杂度= O(exp)

Power()函数为负exp和浮点基数工作。

float power(float base, int exp) {

    if( exp == 0)
       return 1;
    float temp = power(base, exp/2);       
    if (exp%2 == 0)
        return temp*temp;
    else {
        if(exp > 0)
            return base*temp*temp;
        else
            return (temp*temp)/base; //negative exponent computation 
    }

} 

复杂度= O(exp)

这是对平方求幂效率的后续讨论。

这种方法的优点是它在log(n)时间内运行。例如，如果你要计算一个巨大的数，比如x^1048575(2^20 - 1)，你只需要循环20次，而不是使用朴素方法的100万+次。

此外，在代码复杂性方面，它比试图找到最优的乘法序列更简单，这是la Pramod的建议。

编辑:

我想我应该在有人指责我可能会溢出之前澄清一下。这种方法假设您有某种巨大的int库。