# time complexity analysis of recurrence relation [duplicate]

I am not able to solve time complexity analysis of this recurrence relation: T(n)=3T(n/2)+n^2.I want to find time complexity analysis of this recurrence relation without using masters theorem could you please help me to do so.

• Do you want to solve the recurrence or analyse the runtime of evaluating it? What have you tried and where did you get stuck?
– Raphael
Aug 20 '15 at 15:27

Imagine your recurrence as a tree. It has a height of $log_2(n)$ since your input size $n$ is divided by $2$ every time.
The cost for a node on the $ith$-level is $(\frac{n}{2^i})^2$.
On the $ith$-level there are $3^i$ nodes.
The cost for that level (whithout considering the childnodes) ist therefore $3^i*(\frac{n}{2^i})^2$
The overall cost is the sum of the cost for each level that is $\sum_{i=0}^{log_2(n)} (3^i*(\frac{n}{2^i})^2) = \sum_{i=0}^{log_2(n)} (3^i*\frac{n^2}{2^{2i}}) = n^2*\sum_{i=0}^{log_2(n)} (\frac{3^i}{2^{2i}}) = n^2*\sum_{i=0}^{log_2(n)} (\frac{3^i}{4^{i}}) = n^2*\sum_{i=0}^{log_2(n)} (\frac{3}{4})^i$.
Which you can now solve with a formula for a geometric series that gives you $4n^2-3^{log_2(n)+1}$