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  2. Lagrange polynomial - Wikipedia

    en.wikipedia.org/wiki/Lagrange_polynomial

    The interpolation polynomial passes through all four control points, and each scaled basis polynomial passes through its respective control point and is 0 where x corresponds to the other three control points. In numerical analysis, the Lagrange interpolating polynomial is the unique polynomial of lowest degree that interpolates a given set of ...

  3. Linear algebra - Wikipedia

    en.wikipedia.org/wiki/Linear_algebra

    Linear algebra is the branch of mathematics ... at the elementary level, as a subfield of linear algebra. ... Gilbert (2016), Introduction to Linear Algebra (5th ed ...

  4. Outline of linear algebra - Wikipedia

    en.wikipedia.org/wiki/Outline_of_linear_algebra

    This is an outline of topics related to linear algebra, the branch of mathematics concerning linear equations and linear maps and their representations in vector spaces and through matrices. Linear equations

  5. Linear function - Wikipedia

    en.wikipedia.org/wiki/Linear_function

    In mathematics, the term linear function refers to two distinct but related notions: [1]. In calculus and related areas, a linear function is a function whose graph is a straight line, that is, a polynomial function of degree zero or one. [2]

  6. Cramer's rule - Wikipedia

    en.wikipedia.org/wiki/Cramer's_rule

    In linear algebra, Cramer's rule is an explicit formula for the solution of a system of linear equations with as many equations as unknowns, valid whenever the system has a unique solution. It expresses the solution in terms of the determinants of the (square) coefficient matrix and of matrices obtained from it by replacing one column by the ...

  7. System of linear equations - Wikipedia

    en.wikipedia.org/wiki/System_of_linear_equations

    In mathematics, a system of linear equations (or linear system) is a collection of two or more linear equations involving the same variables. [ 1 ] [ 2 ] For example, { 3 x + 2 y − z = 1 2 x − 2 y + 4 z = − 2 − x + 1 2 y − z = 0 {\displaystyle {\begin{cases}3x+2y-z=1\\2x-2y+4z=-2\\-x+{\frac {1}{2}}y-z=0\end{cases}}}

  8. Numerical linear algebra - Wikipedia

    en.wikipedia.org/wiki/Numerical_linear_algebra

    For many problems in applied linear algebra, it is useful to adopt the perspective of a matrix as being a concatenation of column vectors. For example, when solving the linear system =, rather than understanding x as the product of with b, it is helpful to think of x as the vector of coefficients in the linear expansion of b in the basis formed by the columns of A.

  9. Krylov subspace - Wikipedia

    en.wikipedia.org/wiki/Krylov_subspace

    Krylov subspaces are used in algorithms for finding approximate solutions to high-dimensional linear algebra problems. [2] Many linear dynamical system tests in control theory, especially those related to controllability and observability, involve checking the rank of the Krylov subspace.