A Matrix with Orthonormal Columns

In summary, the conversation discusses the proof of the statement that the columns of an n x n matrix M form an orthonormal set if and only if the inverse of M is equal to its transpose, or M^-1 = M^T. The conversation also touches on the definition of orthonormality and provides an example to illustrate the concept.
  • #1
e(ho0n3
1,357
0
Homework Statement
Let M be an n x n matrix. Prove that the columns of M form an orthonormal set if and only if M-1 = MT.

The attempt at a solution
Let's consider the following 2 x 2 matrix

[tex]\begin{pmatrix} a & b \\ c & d \end{pmatrix}[/tex]

If the inverse equals its transpose, i.e.

[tex]\frac{1}{ad - bc} \begin{pmatrix} d & -b \\ -c & a \end{pmatrix} = \begin{pmatrix} a & c \\ b & d \end{pmatrix}[/tex]

then

[tex]\begin{align*}
a & = \frac{d}{ad - bc} \\
b & = \frac{-c}{ad - bc} \\
c & = \frac{-b}{ad - bc} \\
d & = \frac{a}{ad - bc}
\end{align*}[/tex]

or rather that ad - bc = 1. Does this mean that ab + cd = 0? Not necessarily: Consider a = 2 and b = c = d = 1 so that ad - bc = 2 - 1 = 1 but ab + cd = 2 + 1 = 3. What gives?

And doeas ab + cd = 0 imply the equations above for a, b, c and d? I think not.

I'm stumped.
 
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  • #2
Just multiply out the matrices and think.
 
  • #3
[tex]\left| ad - bc \right|=1[/tex], but ad - bc may not necessarily be 1. For example, the columns of [tex]\begin{pmatrix} -1 & 0 \\ 0 & 1 \end{pmatrix}[/tex] are orthonormal, but [tex]det \begin{pmatrix} -1 & 0 \\ 0 & 1 \end{pmatrix}=-1.[/tex] I guess it would be easier to work from the relation [tex]\begin{pmatrix} a & b \\ c & d \end{pmatrix} \begin{pmatrix} a & c \\ b & d \end{pmatrix} = \begin{pmatrix} 1 & 0 \\ 0 & 1 \end{pmatrix}[/tex], which follows from the hypothesis that the transpose of M is its inverse. The equations should be simpler to work with. In general, the product of any 2 x 2 matrix M and its transpose [tex]M^T[/tex] may be expressed as : [tex]\begin{pmatrix} a & b \\ c & d \end{pmatrix} \times \begin{pmatrix} a & c \\ b & d \end{pmatrix} = \begin{pmatrix} (r_1,r_1) & (r_1,r_2) \\ (r_2,r_1) & (r_2,r_2) \end{pmatrix}[/tex], where [tex]r_i[/tex] denotes the ith row of M, and [tex](r_i,r_j)[/tex] denotes the scalar product of [tex]r_i[/tex] and [tex]r_j[/tex]. Now equate the latter expression with the identity matrix. This shows that the rows of M are orthonormal, and the argument can be extended to any (n x n) matrix. To show that the columns are also orthonormal, we could use the fact that if [tex]MM^T = I[/tex], then [tex] M^TM=I[/tex], and thence express the product [tex]M^TM[/tex] as we did above.
 
  • #4
Hi e(ho0n3! :smile:

Why make it so complicated? :rolleyes:

In problems like this, just write out the definition!
e(ho0n3 said:
Let M be an n x n matrix. Prove that the columns of M form an orthonormal set if and only if M-1 = MT.

Hint: MMT = I means, for any i and j, ∑aikajk = Iij.

Put i = j: then … ?

Put i ≠ j: then … ? :smile:
 
  • #5
e(ho0n3 said:
Homework Statement
Let M be an n x n matrix. Prove that the columns of M form an orthonormal set if and only if M-1 = MT.

The attempt at a solution
Let's consider the following 2 x 2 matrix

[tex]\begin{pmatrix} a & b \\ c & d \end{pmatrix}[/tex]

If the inverse equals its transpose, i.e.

[tex]\frac{1}{ad - bc} \begin{pmatrix} d & -b \\ -c & a \end{pmatrix} = \begin{pmatrix} a & c \\ b & d \end{pmatrix}[/tex]

then

[tex]\begin{align*}
a & = \frac{d}{ad - bc} \\
b & = \frac{-c}{ad - bc} \\
c & = \frac{-b}{ad - bc} \\
d & = \frac{a}{ad - bc}
\end{align*}[/tex]

or rather that ad - bc = 1. Does this mean that ab + cd = 0? Not necessarily: Consider a = 2 and b = c = d = 1 so that ad - bc = 2 - 1 = 1 but ab + cd = 2 + 1 = 3. What gives?

And doeas ab + cd = 0 imply the equations above for a, b, c and d? I think not.

I'm stumped.

I don't understand your point with this example. The inverse of
[tex]A= \left[\begin{array}{cc}2 & 1 \\ 1 & 1\end{array}\right][/tex]
is
[tex]A^{-1}= \left[\begin{array}{cc}2 & -1 \\ -1 & 1\end{array}\right][/tex]
NOT the transpose of A and so has nothing to do with this problem.
 
  • #6
OK. Looks like I really messed up on this one. Thank you all for the pointers.
 

FAQ: A Matrix with Orthonormal Columns

What is a matrix with orthonormal columns?

A matrix with orthonormal columns is a matrix in which each column is a unit vector (i.e. has a length of 1) and the dot product of any two different columns is 0. This means that the columns are perpendicular to each other and form a basis for the vector space.

How is a matrix with orthonormal columns useful?

A matrix with orthonormal columns is useful in many applications, such as in linear algebra, signal processing, and data compression. It simplifies calculations and makes it easier to solve systems of equations. It can also be used to represent rotations and reflections in space.

How is a matrix with orthonormal columns different from a regular matrix?

A regular matrix may have columns that are not unit vectors and may not be perpendicular to each other. In contrast, a matrix with orthonormal columns has columns that are unit vectors and are perpendicular to each other. This means that the inverse of a matrix with orthonormal columns is equal to its transpose.

Can a matrix have both orthonormal columns and rows?

Yes, a matrix can have both orthonormal columns and rows. This is known as an orthogonal matrix, where both the columns and rows are unit vectors and are perpendicular to each other. This type of matrix is particularly useful in solving systems of equations and performing transformations.

How do you create a matrix with orthonormal columns?

To create a matrix with orthonormal columns, you can use the Gram-Schmidt process, which is a method for orthonormalizing a set of vectors. Another way is to use the QR decomposition, where the matrix is decomposed into an orthogonal matrix and an upper triangular matrix. You can also manually create a matrix with orthonormal columns by ensuring that each column is a unit vector and that the dot product of any two different columns is 0.

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