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by sdwr
993 days ago
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You kidding me? This is the only reasonable explanation of matrix multiplication. I remember learning it in school, and memorizing how the input dimensions corresponded to output dimensions, without understanding why. This gets to the why perfectly. We all understand how to navigate a 3D space intuitively. If the math doesn't tie into that, it may as well be wizard nonsense. |
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1. For a linear function f, its matrix A for some basis {b_i} is the list of outputs f(b_i). i.e. each column is the image of a basis vector. For an arbitrary vector x, the matrix-vector product Ax = f(x).
2. For two linear functions f,g with appropriate domains/codomains and matrices A,B, the result of "multiplication" BA is the matrix for the composed (also linear) function x -> g(f(x)). For an arbitrary vector x, the product (BA)x = B(Ax) = g(f(x)).
This tells you what a matrix even is and why you multiply rows and columns in the way you do (as opposed to e.g. pointwise). This also tells you why the dimensions are what they are: the codomain has some dimension (the height of the columns) and the domain has some dimension (how many columns are there). For multiplication, you need the codomain of f to match the domain of g for composition to make sense, so obviously dimensions must line up.