I can find the sum of each row (n/log n-i)
and also I can draw its recursive tree but I can't calculate sum of its rows.
T(n)=2T(n/2)+n/logn
T(1) = 1
I can find the sum of each row (n/log n-i)
and also I can draw its recursive tree but I can't calculate sum of its rows.
T(n)=2T(n/2)+n/logn
T(1) = 1
Suppose n = 2^k;
We know for harmonic series (euler formula):
Sum[i = 1 to n](1/i) ~= log(n) [n -> infinity]
t(n) = 2t(n/2) + n/log(n)
= 2(2t(n/4) + n/2/log(n/2)) + n/log(n)
= 4t(n/4) + n/log(n/2) + n/log(n)
= 4(2t(n/8) + n/4/log(n/4)) + n/log(n/2) + n/log(n)
= 8t(n/8) + n/log(n/4) + n/log(n/2) + n/log(n)
= 16t(n/16) + n/log(n/8) + n/log(n/4) + n/log(n/2) + n/log(n)
= n * t(1) + n/log(2) + n/log(4) + ... + n/log(n/2) + n/log(n)
= n(1 + Sum[i = 1 to log(n)](1/log(2^i)))
= n(1 + Sum[i = 1 to log(n)](1/i))
~= n(1 + log(log(n)))
= n + n*log(log(n)))
~= n*log(log(n)) [n -> infinity]
When you start unrolling the recursion, you will get:
Your base case is T(1) = 1
, so this means that n = 2^k
. Substituting you will get:
The second sum behaves the same as harmonic series and therefore can be approximated as log(k)
. Now that k = log(n)
the resulting answer is:
Follow Extended Masters Theorem Below.
Using Extended Masters Theorem T(n)=2T(n/2)+n/logn
can be solved easily as follows.
Here n/log n
part can be rewritten as n * (logn)^-1
,
Effictively maaking value of p=-1.
Now Extended Masters Theorem can be applied easily, it will relate to case 2b of Extended Masters Theorem .
T(n)= O(nloglogn)
Follow this for more detailed explanation
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