问题
The problem
Compute the complexity of this algorithm:
for(i=n; i>1;i=i/2)
for(j=i;j<n;j++){
statement;
}
What have I done on this topic before:
The first loop runs logn times. The second loop runs n-i times with i starting from n and changing to i/2 in each outer loop iteration. So the inner loop runs like this:
n-n 0 times
n - n/2 n/2 times
n - n/4 3n/4 times
n - n/8 7n/8 times
n - n/16 15n/16 times
and so on till
n - 1 times
so the general term is n * ((2^n)-1)/(2^n)
Now this sequence is not arithmetic nor geometric. So formula of n/2 * (a+l) cannot be applied on it. How do I further proceed with this solution or if it is wrong, then what is the correct method.
Note: If n/2*(a+l) is applied, the resulting complexity is -n/(2^n) = O(2^n).
回答1:
You are on the right track. As you mentioned, the inner loop would run log n times. So, the total number of times it runs is:
(n - n/2) + (n - n/4) + ... (log n) times
= n*(log n) - (n/2 + n/4 + n/8 + ... up to 1)
= n*(log n) - n*(1/2 + 1/4 + ...)
<= n*(log n) - n because (1/2 + 1/4 + ...) is 1 even if we take all terms till infinity (G.P)
= n(log n - 1), which is O(n*log(n))
Remember that when calculating complexity, you are always looking for upper bounds, not exact numbers.
回答2:
First the calculations
A := (n - n) + (n - n/2) + (n - n/4) + ... + (n - n / 2^logn) =
log n * (n) - n * (1 + 1/2 + 1/4 + 1/8 + .... 1 / 2 ^ logn)
A > log n * (n) - n * (1 + 1/2 + 1/4 + 1/8 + .... + 1 / 2^infity) =
logn * n - n = n(logn - 2)
A < log n * (n)
As you see I have assigned the expression you want to evaluate to A. From the last two inequations it follows the complexity of your algorithm is thetha(n logn)
Here I used the well known geometric progression of (1 + 1/2 + 1/4 + .....) = 2
回答3:
The exact no of times the statement runs is nlogn - 2n(1-1/2^logn)
来源:https://stackoverflow.com/questions/18932387/complexity-of-two-dependent-for-loops-with-outer-loop-of-log-n-complexity