I am trying to go through the proof of the Master Theorem in Introduction to Algorithms of Cormen, Leiserson, Rivest, Stein (CLRS). The theorem providers an asymptotic analysis for recurrence relations $T(n)=aT(n/b)+f(n)$ where $a\geq 1, b > 1$ and $f(n)$ is an asymptotically positive function.
The authors create a formulation of the following lemma (4.3):
- if $f(n) = \Theta(n^{\log_ba})$, then $g(n)=\Theta(n^{\log_ba}{\log_bn})$
where $g(n) = \sum_{j=0}^{\lfloor \log_b n \rfloor - 1} a^jf(n_j)$ and $n_j = \begin{cases} n, & \text{if j = 0} \\ \lceil n_{j-1}/b \rceil, & \text{if j > 0} \end{cases}$
When it is proving for the situation in which floors and ceilings appear the autrors make a statement:
For case 2, we have $f(n)=\Theta(n^{\log_b a})$. If we can show that $f(n_j) = O(n^{\log_ba}/a^j) = O((n/b^j)^{\log_ba})$, then the proof for case 2 of Lemma 4.3 will go through.
Well, I got it. When this condition is true we can find some constant $c$, such that
$g(n) \le c\sum_{j=0}^{\lfloor \log_b n \rfloor - 1} n^{\log_b a}$
and conclude that $g(n) = O(n^{\log_b a}{\log_bn})$.
But it's not a proof that $g(n) = \Omega(n^{\log_b a}{\log_bn})$. Where is one? Should it be obvious? How can I prove this statement?