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2. Gilbert Strang - Wikipedia

   en.wikipedia.org/wiki/Gilbert_Strang

   William Gilbert Strang (born November 27, 1934 [1]) is an American mathematician known for his contributions to finite element theory, the calculus of variations, wavelet analysis and linear algebra. He has made many contributions to mathematics education, including publishing mathematics textbooks.

3. Elementary matrix - Wikipedia

   en.wikipedia.org/wiki/Elementary_matrix

   The elementary matrices generate the general linear group GL n (F) when F is a field. Left multiplication (pre-multiplication) by an elementary matrix represents elementary row operations, while right multiplication (post-multiplication) represents elementary column operations.

4. Least-squares adjustment - Wikipedia

   en.wikipedia.org/wiki/Least-squares_adjustment

   There are three forms of least squares adjustment: parametric, conditional, and combined: In parametric adjustment, one can find an observation equation h(X) = Y relating observations Y explicitly in terms of parameters X (leading to the A-model below).

5. Linear algebra - Wikipedia

   en.wikipedia.org/wiki/Linear_algebra

   With respect to general linear maps, linear endomorphisms and square matrices have some specific properties that make their study an important part of linear algebra, which is used in many parts of mathematics, including geometric transformations, coordinate changes, quadratic forms, and many other part of mathematics.

6. System of linear equations - Wikipedia

   en.wikipedia.org/wiki/System_of_linear_equations

   Matrix Analysis and Applied Linear Algebra. Society for Industrial and Applied Mathematics (SIAM). ISBN 978-0-89871-454-8. Archived from the original on March 1, 2001. Poole, David (2006). Linear Algebra: A Modern Introduction (2nd ed.). Brooks/Cole. ISBN 0-534-99845-3. Anton, Howard (2005). Elementary Linear Algebra (Applications Version) (9th ...

7. Rank–nullity theorem - Wikipedia

   en.wikipedia.org/wiki/Rank–nullity_theorem

   The rank–nullity theorem is a theorem in linear algebra, which asserts: the number of columns of a matrix M is the sum of the rank of M and the nullity of M ; and the dimension of the domain of a linear transformation f is the sum of the rank of f (the dimension of the image of f ) and the nullity of f (the dimension of the kernel of f ).