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  2. Root-finding algorithm - Wikipedia

    en.wikipedia.org/wiki/Root-finding_algorithm

    Solving an equation f(x) = g(x) is the same as finding the roots of the function h(x) = f(x) – g(x). Thus root-finding algorithms can be used to solve any equation of continuous functions. However, most root-finding algorithms do not guarantee that they will find all roots of a function, and if such an algorithm does not find any root, that ...

  3. Reduced form - Wikipedia

    en.wikipedia.org/wiki/Reduced_form

    The reduced form of the system is: = + = +, with vector of reduced form errors that each depends on all structural errors, where the matrix A must be nonsingular for the reduced form to exist and be unique. Again, each endogenous variable depends on potentially each exogenous variable.

  4. Nondimensionalization - Wikipedia

    en.wikipedia.org/wiki/Nondimensionalization

    Nondimensionalization determines in a systematic manner the characteristic units of a system to use, without relying heavily on prior knowledge of the system's intrinsic properties (one should not confuse characteristic units of a system with natural units of nature). In fact, nondimensionalization can suggest the parameters which should be ...

  5. Newton's method - Wikipedia

    en.wikipedia.org/wiki/Newton's_method

    Since f ′(1) ≠ 0 and f is smooth, it is known that any Newton iteration convergent to 1 will converge quadratically. However, if initialized at 0.5, the first few iterates of Newton's method are approximately 26214, 24904, 23658, 22476, decreasing slowly, with only the 200th iterate being 1.0371.

  6. SAT solver - Wikipedia

    en.wikipedia.org/wiki/SAT_solver

    In computer science and formal methods, a SAT solver is a computer program which aims to solve the Boolean satisfiability problem (SAT). On input a formula over Boolean variables, such as "(x or y) and (x or not y)", a SAT solver outputs whether the formula is satisfiable, meaning that there are possible values of x and y which make the formula true, or unsatisfiable, meaning that there are no ...

  7. Rouché–Capelli theorem - Wikipedia

    en.wikipedia.org/wiki/Rouché–Capelli_theorem

    A system of linear equations with n variables and coefficients in a field K has a solution if and only if its coefficient matrix A and its augmented matrix [A|b] have the same rank. [1] If there are solutions, they form an affine subspace of of dimension n − rank(A). In particular: if n = rank(A), the solution is unique,

  8. System of polynomial equations - Wikipedia

    en.wikipedia.org/wiki/System_of_polynomial_equations

    When solving a system over a finite field k with q elements, one is primarily interested in the solutions in k. As the elements of k are exactly the solutions of the equation x q – x = 0, it suffices, for restricting the solutions to k, to add the equation x i q – x i = 0 for each variable x i.

  9. Basic feasible solution - Wikipedia

    en.wikipedia.org/wiki/Basic_feasible_solution

    A BFS can have less than m non-zero variables; in that case, it can have many different bases, all of which contain the indices of its non-zero variables. 3. A feasible solution x {\displaystyle \mathbf {x} } is basic if-and-only-if the columns of the matrix A K {\displaystyle A_{K}} are linearly independent, where K is the set of indices of ...