The active ideas in linear algebra are often expressed by matrix factorizations\,: S=QΛQTS=Q\Lambda Q^{\mathrm{T}} for symmetric matrices (the spectral theorem) and A=UΣVTA=U\Sigma V^{\mathrm{T}} for all matrices (singular value decomposition). Far back near the beginning comes A=LUA=LU for successful elimination\,: Lower triangular times upper triangular. This paper is one step earlier, with bases in A=CRA=CR for the column space and row space of any matrix -- and a proof that column rank = row rank. The echelon form of AA and the pseudoinverse A+A^+ appear naturally. The ``proofs'' are mostly ``observations''.

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G. Strang. “The Column-Row Factorization of a Matrix.” Journal of Convex Analysis 28 (2021), No. 2, 725–728.