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The transpose

Computing transposes and products like X^T Y, classifying matrices as symmetric or antisymmetric, and proving a matrix that is both must be zero.

Matrix Theory and Linear Algebra, The transpose

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10 exercises

Exercise 4.7.1

Let X=[−1−11]X=\left[\begin{array}{rrr}-1&-1&1\end{array}\right] and Y=[012]Y=\left[\begin{array}{rrr}0&1&2\end{array}\right]. Find XTYX^{T}Y and XYTXY^{T} if possible.

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Exercise 4.7.2

Consider the matrices

Find the following if possible. If it is not possible explain why.

  1. −3AT-3A{{}^{T}}.

  2. 3B−AT3B-A^{T}.

  3. ETBE^{T}B.

  4. EETEE^{T}.

  5. BTBB^{T}B.

  6. CATCA^{T}.

  7. DTBED^{T}BE.

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Exercise 4.7.3

Which of the following matrices are symmetric, antisymmetric, both, or neither?

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Exercise 4.7.4

Suppose AA is a matrix that is both symmetric and antisymmetric. Show that A=0A=0.

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Exercise 4.7.5

Let AA be an n×nn\times n-matrix. Show AA equals the sum of a symmetric and an antisymmetric matrix. Hint: Show that 12(AT+A)\frac{1}{2}(A^{T}+A) is symmetric and then consider using this as one of the matrices.

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Exercise 4.7.6

Show that the main diagonal of every antisymmetric matrix consists of only zeros. Recall that the main diagonal consists of every entry of the matrix which is of the form aiia_{ii}.

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Exercise 4.7.7

Show that for m×nm\times n-matrices A,BA,B and scalars r,sr,s, the following holds:

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Exercise 4.7.8

Let AA be a real m×nm\times n-matrix and let u∈Rn\mathbf{u}\in\mathbb{R}^{n} and v∈Rm\mathbf{v}\in\mathbb{R}^{m}. Show (Au)⋅v=u⋅(ATv)(A\mathbf{u})\boldsymbol{\cdot}\mathbf{v}=\mathbf{u}\boldsymbol{\cdot}(A^{T}\mathbf{v}).

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Exercise 4.7.9

Show that if AA is an invertible n×nn\times n-matrix, then so is ATA^{T} and (AT)−1=(A−1)T(A^{T})^{-1}=(A^{-1})^{T}.

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Exercise 4.7.10

Suppose AA is invertible and symmetric. Show that A−1A^{-1} is symmetric.

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Adapted from Matrix Theory and Linear Algebra © 2017–2026 Peter Selinger, Lyryx Learning, and Ken Kuttler. Licensed under CC BY 4.0. Source: Matrix Theory and Linear Algebra. Imported at revision d74bc3a.