10.1: Coordinate Vectors
- Page ID
- 247
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\(\newcommand{\avec}{\mathbf a}\) \(\newcommand{\bvec}{\mathbf b}\) \(\newcommand{\cvec}{\mathbf c}\) \(\newcommand{\dvec}{\mathbf d}\) \(\newcommand{\dtil}{\widetilde{\mathbf d}}\) \(\newcommand{\evec}{\mathbf e}\) \(\newcommand{\fvec}{\mathbf f}\) \(\newcommand{\nvec}{\mathbf n}\) \(\newcommand{\pvec}{\mathbf p}\) \(\newcommand{\qvec}{\mathbf q}\) \(\newcommand{\svec}{\mathbf s}\) \(\newcommand{\tvec}{\mathbf t}\) \(\newcommand{\uvec}{\mathbf u}\) \(\newcommand{\vvec}{\mathbf v}\) \(\newcommand{\wvec}{\mathbf w}\) \(\newcommand{\xvec}{\mathbf x}\) \(\newcommand{\yvec}{\mathbf y}\) \(\newcommand{\zvec}{\mathbf z}\) \(\newcommand{\rvec}{\mathbf r}\) \(\newcommand{\mvec}{\mathbf m}\) \(\newcommand{\zerovec}{\mathbf 0}\) \(\newcommand{\onevec}{\mathbf 1}\) \(\newcommand{\real}{\mathbb R}\) \(\newcommand{\twovec}[2]{\left[\begin{array}{r}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\ctwovec}[2]{\left[\begin{array}{c}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\threevec}[3]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\cthreevec}[3]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\fourvec}[4]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\cfourvec}[4]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\fivevec}[5]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\cfivevec}[5]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\mattwo}[4]{\left[\begin{array}{rr}#1 \amp #2 \\ #3 \amp #4 \\ \end{array}\right]}\) \(\newcommand{\laspan}[1]{\text{Span}\{#1\}}\) \(\newcommand{\bcal}{\cal B}\) \(\newcommand{\ccal}{\cal C}\) \(\newcommand{\scal}{\cal S}\) \(\newcommand{\wcal}{\cal W}\) \(\newcommand{\ecal}{\cal E}\) \(\newcommand{\coords}[2]{\left\{#1\right\}_{#2}}\) \(\newcommand{\gray}[1]{\color{gray}{#1}}\) \(\newcommand{\lgray}[1]{\color{lightgray}{#1}}\) \(\newcommand{\rank}{\operatorname{rank}}\) \(\newcommand{\row}{\text{Row}}\) \(\newcommand{\col}{\text{Col}}\) \(\renewcommand{\row}{\text{Row}}\) \(\newcommand{\nul}{\text{Nul}}\) \(\newcommand{\var}{\text{Var}}\) \(\newcommand{\corr}{\text{corr}}\) \(\newcommand{\len}[1]{\left|#1\right|}\) \(\newcommand{\bbar}{\overline{\bvec}}\) \(\newcommand{\bhat}{\widehat{\bvec}}\) \(\newcommand{\bperp}{\bvec^\perp}\) \(\newcommand{\xhat}{\widehat{\xvec}}\) \(\newcommand{\vhat}{\widehat{\vvec}}\) \(\newcommand{\uhat}{\widehat{\uvec}}\) \(\newcommand{\what}{\widehat{\wvec}}\) \(\newcommand{\Sighat}{\widehat{\Sigma}}\) \(\newcommand{\lt}{<}\) \(\newcommand{\gt}{>}\) \(\newcommand{\amp}{&}\) \(\definecolor{fillinmathshade}{gray}{0.9}\)Let \(V\) be a finite-dimensional inner product space with inner product \(\inner{\cdot}{\cdot}\) and dimension \(\dim(V)=n\). Then \(V\) has an orthonormal basis \(e=(e_1,\ldots,e_n)\), and, according to Theorem9.4.6~\ref{thm:ParsevalsIdentity}, every \(v\in V\) can be written as
\begin{equation*} v = \sum_{i=1}^n \inner{v}{e_i} e_i. \end{equation*}
This induces a map
\begin{equation*}
\begin{split}
[\,\cdot\,]_e : V &\to \mathbb{F}^n\\
v &\mapsto \begin{bmatrix}
\inner{v}{e_1}\\ \vdots \\ \inner{v}{e_n} \end{bmatrix},
\end{split}
\end{equation*}
which maps the vector \(v\in V\) to the \(n\times 1\) column vector of its coordinates with respect to the basis \(e\). The column vector \([v]_e\) is called the coordinate vector of \(v\) with respect to the basis \(e\).
Example \(\PageIndex{1}\):
Recall that the vector space \(\mathbb{R}_1[x]\) of polynomials over \(\mathbb{R}\) of degree at most 1 is an inner product space with inner product defined by
\begin{equation*}
\inner{f}{g} = \int_0^1 f(x)g(x)dx.
\end{equation*}
Then \(e=(1,\sqrt{3}(-1+2x))\) forms an orthonormal basis for \(\mathbb{R}_1[x]\). The coordinate vector of the polynomial \(p(x)=3x+2\in \mathbb{R}_1[x]\) is, e.g.,
\[ [p(x)]_e= \frac{1}{2} \begin{bmatrix} 7 \\ \sqrt{3} \end{bmatrix}. \]
Note also that the map \([\,\cdot\,]_e\) is an isomorphism (meaning that it is an injective and surjective linear map) and that it is also inner product preserving. Denote the usual inner product on \(\mathbb{F}^n\) by
\begin{equation*}
\inner{x}{y}_{\mathbb{F}^n} = \sum_{k=1}^n x_k \overline{y}_k.
\end{equation*}
Then
\begin{equation*}
\inner{v}{w}_V = \inner{[v]_e}{[w]_e}_{\mathbb{F}^n}, \qquad \text{for all \(v,w\in V\),}
\end{equation*}
since
\begin{multline*}
\inner{v}{w}_V = \sum_{i,j=1}^n \inner{\inner{v}{e_i} e_i}{\inner{w}{e_j}e_j}
= \sum_{i,j=1}^n \inner{v}{e_i} \overline{\inner{w}{e_j}} \inner{e_i}{e_j}\\
= \sum_{i,j=1}^n \inner{v}{e_i} \overline{\inner{w}{e_j}} \delta_{ij}
= \sum_{i=1}^n \inner{v}{e_i} \overline{\inner{w}{e_i}} = \inner{[v]_e}{[w]_e}_{\mathbb{F}^n}.
\end{multline*}
It is important to remember that the map \([\,\cdot\,]_e\) depends on the choice of basis \(e=(e_1,\ldots,e_n)\).
Contributors
- Isaiah Lankham, Mathematics Department at UC Davis
- Bruno Nachtergaele, Mathematics Department at UC Davis
- Anne Schilling, Mathematics Department at UC Davis
Both hardbound and softbound versions of this textbook are available online at WorldScientific.com.