How to Solve for a 3x3 Matrix Using A and B Vectors?

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In summary, the conversation discusses the process of reconstructing a 3x3 matrix M using data that can be described by the equation M*A = B. The speaker has tried using 9 pairs of vectors for A and B to yield the coefficients of M, but has not been successful. They are seeking advice on how to properly reconstruct the matrix using Mathematica or MATLAB. It is determined that they need three linearly independent vectors to accurately reconstruct the matrix.
  • #1
DivGradCurl
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Hi all,

I have this data that can be described by M*A = B, where M is a 3x3 matrix and A and B are 3x1 vectors.

Since I know and can collect A and B data, and I have 9 unknowns in the 3x3 matrix, I thought that collecting 9 pairs of A and B vectors would yield the matrix M's coefficients via 9 equations.

However, it has not been the case. For whatever reason, I'm not getting those coefficients. Is there something you recommend looking into?

I have both Mathematica and Matlab. It's very possible I'm not considering or overlooking a linear algebra principle. I just tried Solve in Mathematica, and I get { }, which is a meaningless, or better :confused: response!

Thank you
 
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  • #2
How are you trying to reconstruct the matrix? As long as your choices of the vectors the matrix act on is linearly independent you should be able to make a full reconstruction.

Another possibility is that your Mathematica code is wrong.
 
  • #3
Hi,

I'm trying to reconstruct the matrix M with Mathematica's Solve[ ]:

The vectors are basically (x, y ,z) and (x' , y' , z') coordinates

Screen_Shot_2016_04_06_at_9_47_43_PM.png


And the data behind this mess is here - shown in (x,y,z) row sets - where the "M4" and "IF" would be like A and B in M*A = B. The data looks linearly independent:

Screen_Shot_2016_04_06_at_9_48_15_PM.png


So, I don't know why I'm getting those empty brackets in Mathematica. Maybe I should explicitly write each equation, but I'm assuming Mathematica can handle that.
 
  • #4
I managed to find a number of the elements by rewriting my Solve[ ] call:

Screen_Shot_2016_04_06_at_10_08_08_PM.png


And, as you can see above, I'm left with the first column vector within M, i.e. [m11; m21; m31], left to be determined.

To be honest, I don't understand why I have those 3 elements left to be determined. Using vector rows beyond row 2 (i.e. k > 2) are giving open brackets solutions.

Mathematica! :nb)
 
  • #5
You are using too many vectors and so they are not linearly independent. Since you have numerical values you are likely getting rounding errors, making the system undetermined. Since you have only used vectors with x value zero, you are getting an undetermined first column.

You need to use three linearly independent vectors.
 
  • #6
I get you; makes sense now! I also see what you mean by the three linear independent vectors as [1; 0; 0], [0; 1; 0], and [0;0;1]. They give away 3 columns of M.

Too bad the system I'm crunching this data through doesn't have that level of direct control, so I need to get as close as possible to those 3 vectors for "A" in M*A = B. Hard to predict I will get those vectors, but I'll try. If I do, I will have the "B" vectors as well, and it will be the end of it.

Do you happen to know if there is a hack "brute force" method :smile: with linearly dependent vectors? I would guess MATLAB has something like this. Reminds me of pseudo-inverse techniques, but I'm not looking for an inverse.
 
  • #7
No, if you do not have three linearly independent vectors you do not have enough information to reconstruct the matrix.

Note: They do not need to be orthogonal, just linearly independent.
 
  • #8
Oroduin is correct. There is no unique answer. For example taking the cross product between the two vector yields another vector. A orthogonal rotation about this vector axis by 90 degrees will transform one vector into the other. That is one way to get a matrix. However, you could equally well take a unit vector in the direction a + b. This yields another vector c. Now a rotation of 180 degrees about c transforms a into a multiple of b. Now rescale the matrix to transform a into b.
 
  • #9
Sorry, I misunderstood
 

1. What is a 3x3 matrix?

A 3x3 matrix is a rectangular array of numbers or variables arranged in three rows and three columns. It is a mathematical tool used to represent and solve systems of equations and perform operations in linear algebra.

2. How do you solve for a 3x3 matrix?

To solve for a 3x3 matrix, you can use different methods such as Gaussian elimination, Cramer's rule, or matrix inversion. These methods involve manipulating the matrix through row operations to reduce it to its simplest form and then using algebraic techniques to find the solution.

3. What is the importance of solving for a 3x3 matrix?

Solving for a 3x3 matrix is important in many fields such as physics, engineering, and computer science. It allows us to solve complex systems of equations and perform transformations in three-dimensional space, making it a valuable tool in problem-solving and decision-making processes.

4. Can a 3x3 matrix have more than one solution?

Yes, a 3x3 matrix can have multiple solutions. This is known as an indeterminate system, where there are more variables than equations. In this case, the matrix can have an infinite number of solutions, and it is necessary to use additional information or constraints to find a unique solution.

5. Are there any tips for solving a 3x3 matrix efficiently?

One tip for solving a 3x3 matrix efficiently is to use the properties of row operations to manipulate the matrix and reduce it to its simplest form. Another tip is to use a calculator or software program to perform the calculations accurately and save time. It is also helpful to practice and familiarize oneself with different methods of solving 3x3 matrices to become more efficient at it.

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