\begin{definition}[Definition:Dot Product/Definition 1]
Let $\mathbf a$ and $\mathbf b$ be vectors in a vector space $\mathbf V$ of $n$ dimensions:
{{begin-eqn}}
{{eqn | l = \mathbf a
      | r = \sum_{k \mathop = 1}^n a_k \mathbf e_k
}}
{{eqn | l = \mathbf b
      | r = \sum_{k \mathop = 1}^n b_k \mathbf e_k
}}
{{end-eqn}}
where $\tuple {\mathbf e_1, \mathbf e_2, \ldots, \mathbf e_n}$ is the standard ordered basis of $\mathbf V$.
The '''dot product''' of $\mathbf a$ and $\mathbf b$ is defined as:
:$\ds \mathbf a \cdot \mathbf b = a_1 b_1 + a_2 b_2 + \cdots + a_n b_n = \sum_{i \mathop = 1}^n a_i b_i$
If the vectors are represented as column matrices:
:$\mathbf a = \begin {bmatrix} a_1 \\ a_2 \\ \vdots \\ a_n \end {bmatrix} , \mathbf b = \begin {bmatrix} b_1 \\ b_2 \\ \vdots \\ b_n \end {bmatrix}$
we can express the dot product as:
:$\mathbf a \cdot \mathbf b = \mathbf a^\intercal \mathbf b$
where:
:$\mathbf a^\intercal = \begin {bmatrix} a_1 & a_2 & \cdots & a_n \end {bmatrix}$ is the transpose of $\mathbf a$
:the operation between the matrices is the matrix product.
\end{definition}