How to compute the rotation matrix

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SUMMARY

The discussion focuses on computing a rotation matrix R that transforms one 4x3 matrix X0 into another matrix X, expressed as X = R * X0. Participants clarify that a rotation matrix must be square and orthogonal with a determinant of 1. The problem is framed as finding such a matrix R under the condition that A^T A = B^T B, where A and B are the given matrices. The Gram-Schmidt orthogonalization method is suggested as a potential solution, alongside the Helmert transformation for coordinate transformation.

PREREQUISITES
  • Understanding of matrix dimensions and properties, specifically 4x3 matrices.
  • Knowledge of orthogonal matrices and their properties, including determinants.
  • Familiarity with Gram-Schmidt orthogonalization technique.
  • Basic concepts of coordinate transformations in linear algebra.
NEXT STEPS
  • Study the Gram-Schmidt orthogonalization process in detail.
  • Research the Helmert transformation and its applications in coordinate transformations.
  • Explore the properties of orthogonal matrices and their determinants.
  • Learn about the Hilbert-Schmidt orthogonalization method for solving matrix equations.
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Mathematicians, data scientists, and engineers involved in linear algebra, particularly those working with transformations and matrix computations in higher dimensions.

Renoald
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Hai , I have two matrix , let say X=[ A1 A2 A3
A4 A5 A5
A7 A8 A9
A10 A11 A12]
and X0=[B1 B2 B3
B4 B5 B6
B7 B8 B9
B10 B11 B12]

Can anyone show me how to compute the rotation matrix from X and X0 ?
Thank You
 
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Hey Renoald and welcome to the forums.

One problem that you have is that a rotation matrix preserves the dimension and is a basis which means that the matrix has to be square (even if some values don't contribute in the form of zero entries).

I think it would be helpful if you gave the exact dimensions of your matrices for X and X0. If these are vectors in a Euclidean space, then this is a very well understood problem, but if they are matrices then we will need a more general result.

So let's say X is a matrix with 3 rows and 2 columns, X will be a 3x2 matrix.
 
Hai , Thank You for reply!
The dimension of X and X0 is 4 x 3 ( Matrix form) and This is not a square matrix.
Let Say X=RX0 , then the rotation matrix is R . How to compute the R ?
Thank You ...
 
I am afraid you are going to have to explain what you mean by "rotating" one matrix to another.
 
Hi Renoald.

In \mathbb R^n the term "rotation" usually means an orthogonal matrix with the determinant 1 (the determinant of an orthogonal matrix is always 1 or -1).

So, as far as I understand your question is: given two 4\times 3 matrices A and B find a rotation (an orthogonal matrix with determinant 1) R such that B=RA. And your matrices have real entries. Am I correct here?

Note that such R does not always exists: for 2 real matrices A and B one can find an orthogonal matrix R such that B=RA if and only if A^T A =B^T B, where A^T is the transpose of A. So I assume your matrices satisfy this condition; if not, you are lucky, because such R does not exists, and you do not have to do anything :)

Probably the easiest way to find R is to apply Gram-Schmidt orthogonalization to the columns of one of the matrices (say A). If you know what it is, I can tell you what to do; if not, you have to learn it first.
 
Hai , thank you for the reply.
example i give here is what called as coordinate transformation.
I not sure Gram-Schmidt orthogonalization can used to resolve this problem or not !
as what i search by google , the solution given is Helmert transformation.
Any one have idea about this ?
 
Renoald,
if you want to get help, then STATE the problem first.

Am I correct, that translated to the mathematical language you problem can be stated like that:
given two 4×3 matrices A and B (with real entries) find a rotation (an orthogonal matrix with determinant 1) R such that B=RA?

If that is the statement, then the problem CAN be solved using Hilbert-Schmidt orthogonalization.

If that is not the statement, you should STATE the problem first: in particular, what do you mean by rotation in 4-dimensional space?
 

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