I have some recurrence relationships I use to compute some coefficients of a series. I want to know what the time complexity of computing these is. Suppose I know the coefficients $a_0,...,a_n$, and I want to compute $c_0,...,c_n$ as follows
$ c_{n}=\begin{cases} e^{b_{0}}, & n=0\\ \frac{1}{n}\sum_{k=1}^{n}kb_{k}c_{n-k}, & n\geq1 \end{cases}$
where
$b_{n}=\begin{cases} \frac{1}{a_{0}}, & n=0\\ -\frac{1}{a_{0}}\sum_{i=1}^{n}a_{i}b_{n-i}, & n\geq1 \end{cases}$
So far this is what I have. If we know $b_0,...,b_{k-1}$ then $b_k$ can be computed in $O(k)$ time, so to compute $b_0,...,b_{n}$ takes $\sum_{k=0}^{n}O(k)=O(n^2)$ time.
Now suppose that we know $b_0,...,b_{k}$ and $c_0,...,c_{k-1}$ then it takes $O(k)$ time to compute $c_k$. Thus to compute $c_0,...,c_{n}$ it takes $\sum_{k=0}^{n}O(k)=O(n^2)$. Ofcourse we have to take into account the time it takes to compute $b_0,...,b_{n}$ which is $O(n^2)$.
So can I conclude that the time it takes to compute $c_0,...,c_{n}$ is
$O(n^2)+O(n^2)=O(n^2)$??