- #1
DuckAmuck
- 238
- 40
For example, does this always hold true?
M_ab = v_a × w_b
If not, where does it break down?
M_ab = v_a × w_b
If not, where does it break down?
hilbert2 said:Let's say there are a column vector ##A = \begin{bmatrix}a \\ b\end{bmatrix}## and row vector ##B = \begin{bmatrix}c & d\end{bmatrix}## that have
##AB = \begin{bmatrix}ac & ad \\ bc & bd\end{bmatrix} = \begin{bmatrix}0 & 1 \\ 1 & 0\end{bmatrix}##.
Is this possible, knowing that ##xy = 0## for real numbers ##x,y## implies that either ##x=0## or ##y=0## ?
It can always be done by a linear combination of those where ##\operatorname{rank}M## is the minimal length of it.DuckAmuck said:For example, does this always hold true?
M_ab = v_a × w_b
If not, where does it break down?
DuckAmuck said:For example, does this always hold true?
M_ab = v_a × w_b
If not, where does it break down?
Sure, they are rank one matrices.hilbert2 said:Also, I guess the determinant of this kind of matrices (if they're square) is always zero, as the columns are multiples of each other. This is a very limiting property for a matrix.
fresh_42 said:The question gets interesting, if we ask for the minimal length of linear combinations of ##x\otimes y \otimes z## to represent a given bilinear mapping, e.g. matrix multiplication. If we define the matrix exponent ## \omega := \min\{\,\gamma\,|\,(A;B) \longmapsto A\cdot B = \sum_{i}^Rx_i(A) \otimes y_i(B) \otimes Z_i \,\wedge \, R=O(n^\gamma)\,\} ## then ##2\leq \omega \leq 2.3727## and we do not know how close we can come to the lower bound.
No, not every matrix can be expressed as the product of two vectors. This is because the dimensions of the matrix and the vectors must match in order for the product to be possible.
The matrix must be a square matrix, meaning it has an equal number of rows and columns, and the vectors must have the same number of elements as the dimensions of the matrix.
To find the vectors that can express a given matrix, you can use a process called matrix decomposition. This involves finding the eigenvectors and eigenvalues of the matrix and using them to create the vectors.
Yes, there is a unique solution for expressing a matrix as the product of two vectors. This is because the eigenvectors and eigenvalues used in the matrix decomposition process are unique and determine the vectors that can express the matrix.
Yes, a matrix can be expressed as the product of more than two vectors. However, the number of vectors needed will depend on the dimensions of the matrix and the desired outcome.