Given the matrix A:
a) Find orthonormal vectors q1, q2 and q3 as combinations of the linearly independent columns of the given matrix A.
b) Write the given matrix A=QR.

{: @super_structure nope, not eigenvectors. in this case, i'm looking for three orthonormal vectors that would make solving Ax=b much more simple, should b be provided. it is a precursor to eigenvalues and eighenvectors though.

i'll give you a hint. if you compute the dot product of q1 with q2 or q3, what do you get? also, what is the length of these vectors? :}

{: @mackle it's just my staple for comments. nothing more. ':}' appears to be a bearded smiley, so i ran with it, blocking my comments with an opening beard and closing beard. :}

Gramâ€“Schmidt is the only think I could think of that makes sense, and I had to cheat and look that up. Not an algorithm I ever used (or at least that I knew by name).

While a structural engineering student, I essentially dealt with matrices of special characteristics. Particularly, stiffness matrices which are symmetric, positive matrices. Therefore, we pretty much used the Cholesky decomposition and the Jacobi method for finding the inverse and Eigenvector(s).

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