Σ from i=1 to n of(n)(n+1)/2
What is the upper limit of computation for a give n? is it O(n^3) O(n^2)?
Example:
n=1 , sum =1
n=2 , sum= 1+ 1+2 , sum = 4
n=3, sum= 1+1+2+1+2+3开发者_如何学JAVA, sum = 10
n=4, sum = 1 + 1+2 + 1+2+3 + 1+2+3+4 = 20
n= 5, sum = 1+ 1+2 +1+2+3 +1+2+3+4 + 1+2+3+4+5 , sum = 35
...
n=10, sum = ..... , sum = 220
etc, so what is the upper bound of this computation as a function of N? is it :
O(n^3)?
I presume that you mean Σ1 ≤ i ≤ n i(i + 1)/2, since Σ1 ≤ i ≤ n n(n + 1)/2 is just n²(n + 1)/2, which I'm sure you could have seen for yourself.
Anyway, why should you put up with mere asymptotic growth rates when you can compute the sum exactly?
Σ1 ≤ i ≤ n i(i + 1)/2
= ½ Σ1 ≤ i ≤ n (i² + i)
= ½ (n(n + 1)(2n + 1)/6 + n(n + 1)/2)
= n³/6 + n²/2 + n/3
The OEIS calls these numbers (1, 4, 10, 20, ...) the "tetrahedral numbers".
It is O(n^3).
To see that this is true you can visualize it as a triangular pyramid.
We can approximate n(n+1)/2
to n^2
. So our sum is 1^2 + 2^2 + ... + n^2
, and that is n(n+1)(2n+1)/6
, which can be approximated to n^3
. So the upper bound is n^3
.
The exact formula for the sum is 1/6*n*(n+1)*(n+2)
, which is O(n^3)
.
Yes, summing some polynomial of degree d over k = 1,2,...,n yields a polynomial in n of degree d+1. Since k(k+1) / 2
is of degree 2 in k, its sum is of degree 2 + 1 = 3 in n.
Are you asking for computation complexity of the following sum, or for the big-O bound for the sum?
The second is O(n^3), like people already noticed, but to compute the sum you only need linear amount of additions and multiplications. You can regroup the summands and rewrite the sum as
n*1 + (n-1)*2 + ... + 1*n
from where it is clear that the sum can be computed in O(n).
Oh, and Gareth noted that there is closed-form expression for the sum, which computes in constant time.
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