I have the expression
$y_i = \displaystyle\sum_j x_j \!\cdot\!a_{ij} \!\cdot\! \exp \Big(\sum_k b_{ijk} \!\cdot\! x_k \Big)$
which I want to shorten without introducing more notation than necessary. For example, $\displaystyle\,y_i = \sum_j a_{ij}\! \cdot\! x_j\,$ can be written as $\,\vec{y} = A \,\vec{x}\,$ without any further explanation.
So what about this expression for the first sum above,
$\vec{y} = \Big(A \!\circ\! \exp\big(\, \underline{B} \!\cdot \!\vec{x} \,\big) \Big) \!\cdot\! \vec{x}$
where $A$ is the matrix with entries $a_{ij}$ and $B$ is the 3rd order tensor-like thing with entries $b_{ijk}$? Of course, $\exp$ is taken element-wise.
I am saying tensor-like because I am not sure which notation I would have to use when I were to use tensor index notation – for example, $b^{ij}_k$ or $b^i_{jk}$. All beginner articles about tensor notation seem to use the concept of a changing basis to determine which index goes super- or subscript; however, I only have one single basis, so proceeding like this does not really help me.
Update: I think my main question is this: If $\,\underline{B}\,$ is a 3rd order tensor and $\,x\,$ a vector, is it obvious (or usually assumed) that $\,\displaystyle\underline{B} \!\cdot\!\vec{x} = \sum_k b_{ijk}\!\cdot\!x_k $? Or could this be understood as $\,\sum_j b_{ijk}\!\cdot\!x_j\,$ or even $\,\displaystyle\sum_i b_{ijk}\!\cdot\!x_i$?
Another update: Similar to the above: What about $\,\vec{x}^{\,T} \!\!\!\cdot\! \underline{B}$? I understand that as $\,\displaystyle\sum_i x_i \!\cdot\!b_{ijk}$, but is this obvious?