• Title: Gramian Matrix

  • Series: Abstract Linear Algebra

  • Chapter: General inner products

  • YouTube-Title: Abstract Linear Algebra 16 | Gramian Matrix

  • Bright video: https://youtu.be/nokLWUK9dwM

  • Dark video: https://youtu.be/guZzM62MTwo

  • Quiz: Test your knowledge

  • PDF: Download PDF version of the bright video

  • Dark-PDF: Download PDF version of the dark video

  • Print-PDF: Download printable PDF version

  • Thumbnail (bright): Download PNG

  • Thumbnail (dark): Download PNG

  • Subtitle on GitHub: ala16_sub_eng.srt missing

  • Timestamps (n/a)
  • Subtitle in English (n/a)
  • Quiz Content

    Q1: Let $V$ be a $\mathbb{F}$-vector space with inner product $\langle \cdot, \cdot \rangle$ and $U \subseteq V$ be a subspace with basis $\mathcal{B} = (b_1, b_2, \ldots, b_k)$. What is always correct for the Gramian matrix $G(\mathcal{B})$?

    A1: $G(\mathcal{B})$ is a $(k \times k)$-matrix.

    A2: $G(\mathcal{B})$ has only real entries.

    A3: $G(\mathcal{B})$ is singular.

    A4: $G(\mathcal{B})$ is not a selfadjoint matrix.

    Q2: Let $V$ be a $\mathbb{F}$-vector space with inner product $\langle \cdot, \cdot \rangle$ and $U \subseteq V$ be a subspace with basis $\mathcal{B} = (b_1, b_2, \ldots, b_k)$. Is the Gramian matrix $G(\mathcal{B})$ invertible?

    A1: Yes, always!

    A2: Only in the case that $\mathcal{B}$ is an ONB.

    A3: Only if $\mathbb{F} = \mathbb{R}$.

    A4: No, never!

    Q3: Let $V$ be a $\mathbb{F}$-vector space with inner product $\langle \cdot, \cdot \rangle$ and $U \subseteq V$ be a subspace with basis $\mathcal{B} = (b_1, b_2, \ldots, b_k)$. The Gramian matrix $G(\mathcal{B})$ can be used the calculate the orthogonal projection of $x \in V$ onto $U$. How do we do that?

    A1: Calculate $G(\mathcal{B})^{-1} \begin{pmatrix} \langle b_1, x \rangle \ \vdots \ \langle b_k, x \rangle \end{pmatrix}$ to get the coordinate vector of the orthogonal projection.

    A2: Calculate $G(\mathcal{B}) \begin{pmatrix} \langle b_1, x \rangle \ \vdots \ \langle b_k, x \rangle \end{pmatrix}$ to get the coordinate vector of the normal component.

    A3: Solve the system with $G(\mathcal{B})$ on the left-hand side and $\begin{pmatrix} \langle b_1, x \rangle \ \vdots \ \langle b_k, x \rangle \end{pmatrix}$ on the right-hand side to get the coordinates of the normal component.

    A4: Calculate $G(\mathcal{B}) \begin{pmatrix} \langle b_1, b_1 \rangle \ \vdots \ \langle b_k, b_k \rangle \end{pmatrix}$ to get the coordinates of the orthogonal projection.

  • Back to overview page