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  2. Linear inequality - Wikipedia

    en.wikipedia.org/wiki/Linear_inequality

    Two-dimensional linear inequalities are expressions in two variables of the form: + < +, where the inequalities may either be strict or not. The solution set of such an inequality can be graphically represented by a half-plane (all the points on one "side" of a fixed line) in the Euclidean plane. [2]

  3. Inequation - Wikipedia

    en.wikipedia.org/wiki/Inequation

    Computer support in solving inequations is described in constraint programming; in particular, the simplex algorithm finds optimal solutions of linear inequations. [6] The programming language Prolog III also supports solving algorithms for particular classes of inequalities (and other relations) as a basic language feature.

  4. Inequality (mathematics) - Wikipedia

    en.wikipedia.org/wiki/Inequality_(mathematics)

    When solving inequalities using chained notation, it is possible and sometimes necessary to evaluate the terms independently. For instance, to solve the inequality 4 x < 2 x + 1 ≤ 3 x + 2, it is not possible to isolate x in any one part of the inequality through addition or subtraction.

  5. Karush–Kuhn–Tucker conditions - Wikipedia

    en.wikipedia.org/wiki/Karush–Kuhn–Tucker...

    The system of equations and inequalities corresponding to the KKT conditions is usually not solved directly, except in the few special cases where a closed-form solution can be derived analytically. In general, many optimization algorithms can be interpreted as methods for numerically solving the KKT system of equations and inequalities.

  6. Gaussian elimination - Wikipedia

    en.wikipedia.org/wiki/Gaussian_elimination

    Once y is also eliminated from the third row, the result is a system of linear equations in triangular form, and so the first part of the algorithm is complete. From a computational point of view, it is faster to solve the variables in reverse order, a process known as back-substitution. One sees the solution is z = −1, y = 3, and x = 2. So ...

  7. Linear matrix inequality - Wikipedia

    en.wikipedia.org/wiki/Linear_matrix_inequality

    In convex optimization, a linear matrix inequality (LMI) is an expression of the form ⁡ ():= + + + + where = [, =, …,] is a real vector,,,, …, are symmetric matrices, is a generalized inequality meaning is a positive semidefinite matrix belonging to the positive semidefinite cone + in the subspace of symmetric matrices .

  8. Khan Academy - Wikipedia

    en.wikipedia.org/wiki/Khan_Academy

    Khan Academy is an American non-profit [3] educational organization created in 2006 by Sal Khan. [1] Its goal is to create a set of online tools that help educate students. [ 4 ] The organization produces short video lessons. [ 5 ]

  9. Trace inequality - Wikipedia

    en.wikipedia.org/wiki/Trace_inequality

    In mathematics, there are many kinds of inequalities involving matrices and linear operators on Hilbert spaces. This article covers some important operator inequalities connected with traces of matrices. [1] [2] [3] [4]

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