I’ve got the following recursion:
T(n) = T(n/3) + T(2n/3) + O(n)
The height of the tree would be log3/2 of 2. Now the recursion tree for this recurrence is not a complete binary tree. It has missing nodes lower down. This makes sense to me, however I don’t understand how the following small omega notation relates to the cost of all leaves in the tree.
“… the total cost of all leaves would then be Theta (n^log3/2 of 2) which, since log3/2 of 2 is a constant strictly greater then 1, is small omega(n lg n).”
Can someone please help me understand how the Theta(n^log3/2 of 2) becomes small omega(n lg n)?
OK, to answer your explicit question about why
n^(log_1.5(2))isomega(n lg n):For all k > 1, n^k grows faster than
n lg n. (Powers grow faster than logs eventually). Therefore since2 > 1.5,log_1.5(2) > 1, and thusn^(log_1.5(2))grows faster thann lg n. And since our function is inTheta(n^(log_1.5(2))), it must also be inomega(n lg n)