Description

For a subspace VV, we define a basis B\mathcal{B} as an ordered set of vectors {v1,v2,,vn}\{\vec{v}_1, \vec{v}_2, \ldots, \vec{v}_n\}, such that

  1. span{v1,v2,,vn}=V\text{span}\{\vec{v}_1, \vec{v}_2, \ldots, \vec{v}_n\} = V and

  2. {v1,v2,,vn}\{\vec{v}_1, \vec{v}_2, \ldots, \vec{v}_n\} is linearly independent.

Because of these properties, we can express any vector in the vector space VV as a linear combination of the basis vectors.

Note: The order of the basis vectors matters for a basis!

If we don't specify a basis, we are usually referring to the standard basis S={[1000],[0100],,[0001]}\mathcal{S} = \left\{\begin{bmatrix}1 \\ 0 \\ 0 \\ \vdots \\ 0\end{bmatrix}, \begin{bmatrix}0 \\ 1 \\ 0 \\ \vdots \\ 0\end{bmatrix}, \ldots, \begin{bmatrix}0 \\ 0 \\ 0 \\ \vdots \\ 1\end{bmatrix}\right\}.

In fact, we have been almost always using the standard basis vectors. For example, let v=[542]\vec{v} = \begin{bmatrix}5 \\ 4 \\ 2\end{bmatrix} in the standard basis.

v=[542]=5[100]+4[010]+2[001]\vec{v} = \begin{bmatrix}5 \\ 4 \\ 2\end{bmatrix} = 5\begin{bmatrix}1 \\ 0 \\ 0\end{bmatrix} + 4\begin{bmatrix}0 \\ 1 \\ 0\end{bmatrix} + 2\begin{bmatrix}0 \\ 0 \\ 1\end{bmatrix}

To be precise, we therefore write

[v]S=[542][\vec{v}]_\mathcal{S} = \begin{bmatrix}5 \\ 4 \\ 2\end{bmatrix}

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