hi I'm a little confused about the log(sum) function and sum(log) function. In special, what's the relationship between these two terms? $$ -\log \sum_{i}a_i\sum_i b_i $$
$$ -\sum_i\log(a_i+b_i) $$
thanks for the comment from @hardmath. here is the original question:
given a negative log-likelihood of an observation set: $$ \mathbf{L}=-\sum_{i,j}\log(\pi_a M_{i,j}+\pi_bN_{i,j}) $$ where C is the constant parameter. $\pi_a$+$\pi_b$=1 are proportion of the two component, given the instance $O_{ij}$.
$\bf{Lemma 1}$ $$ -\log\sum_{k=1}^Kf_k(x)=\min_{\Phi(x)\in \Delta_+}\sum_{k=1}^K\{\Phi_k(x)[\log\Phi_k(x)-log(f_k(x)]\} \\ s.t. \sum\Phi_k(x)=1, \Phi_k(x)\in (0,1) $$
$\bf{proof}$ $$ RHS=\sum_{k=1}^K\Phi_k(x)\log\frac{\Phi_k(x)}{f_k(x)} \\ >=\sum_{k=1}^K\Phi_k(x)\log\frac{\sum_{k=1}^K\Phi_k(x)}{\sum_{k=1}^Kf_k(x)}(log-sum\ inequality) \\ =-\log\sum_{k=1}^Kf_k(x)(\sum\Phi_k(x)=1) $$
Let: $$ \mathit{C}=\sum_{i,j}\Phi^{i,j}_a(\log\Phi^{i,j}_a-\log(\pi_aM_{i,j}))+\Phi^{i,j}_b(\log\Phi^{i,j}_B-\log(\pi_bN_{i,j})) $$ given the constraint, that for each $(i,j)$, $\Phi^{i,j}_a+\Phi^{i,j}_b=1$
Then $\textbf{how to prove:}$
Minimize $C$ equals minimize $L$ ?
following lemma1, we have $$ \min C=-\log\sum(\pi_aM_{i,j})-\log\sum(\pi_bN_{i,j}) $$ then the next step is how to prove the relationship between $\min C$ and $L$?