最大子序列和问题的四种算法

本文介绍了四种不同复杂度的最大子序列和算法实现:O(N^3)、O(N^2)、O(NlogN)及O(N)。通过具体代码展示了如何找出数组中具有最大和的连续子序列。

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算法一,该算法的复杂度为:O(N^3)

int MaxSubsequenceSum( const int A[],int N)
{
    int ThisSum,Maxsum,i,j,k;
    MaxSum = 0;
    for(i = 0; i < N; i++)
        for(j = i; j < N; j++)
        {
            ThisSum = 0;
            for(k = i; k <= j; k++)
                ThisSum += A[k];
            if(ThisSum > MaxSum)
                MaxSum = ThisSum;
        }
    return MaxSum;
}

算法二,该算法的复杂度为:O(N^2)

int MaxSubsequenceSum( const int A[],int N)
{
    int ThisSum,MaxSum,i,j;
    MaxSum = 0;
    for( i = 0; i < N; i++)
    {
        ThisSum = 0;
        for(j = i; j < N;j++)
        {
            ThisSum += A[j];
            if(ThisSum > MaxSum)
                MaxSum = ThisSum;
        }
    }
    return MaxSum;
}

算法三,该算法的复杂度为:O(NlogN)

static int MaxSubSum(const int A[],int Left,int Right)
{
    int MaxLeftSum,MaxRightSum;
    int MaxLeftBorderSum,MaxRightBorderSum;
    int LeftBorderSum,RightBorderSum;
    int Center,i;
    
    if (Left == Right) /* Base Case */
        if (A[Left] > 0)
            return A[Left];
        else
            return 0;
    Center = (Left + Right)/2;
    MaxLeftSum = MaxSubSum(A,Left,Center);
    MaxRightSum = MaxSubSum(A,Center+1,Right);
   
    MaxLeftBorderSum = 0;
    LeftBorderSum = 0;
    for(i = Center; i >= Left; i--)
    {
       LeftBorderSum += A[i];
          if(LeftBorderSum > MaxLeftBorderSum)
            MaxLeftBorderSum = LeftBorderSum;
    }
   
    MaxRightBorderSum = 0;
    RightBorderSum = 0;
    for(i = Center + 1; i <= Right; i++)
    {
      RightBorderSum += A[i];
         if(RightBorderSum > MaxRightBorderSum)
            MaxRightBorderSum = RightBorderSum;
   }
   
   return Max3(MaxLeftSum,MaxRightSum,MaxLeftBorderSum + MaxRightBorderSum);
}
int MaxSubsequenceSum(const int A[],int N)
{
    return MaxSubSum(A,0,N-1);
}

算法四,该算法的复杂度为:O(N)

int MaxSubsequenceSum(const int A[],int N)
{
    int ThisSum,MaxSum,j;
    ThisSum = MaxSum = 0;
    for(j =0; j < N; j++)
    {
        ThisSum += A[j];
        if(ThisSum > MaxSum)
            MaxSum = ThisSum;
        else if(ThisSum < 0)
            ThisSum = 0;
    }
    return MaxSum;
}

转载于:https://www.cnblogs.com/y3w3l/p/6349365.html

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