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  2. Vector (video game) - Wikipedia

    en.wikipedia.org/wiki/Vector_(video_game)

    Damien McFerran of Pocket Gamer rated 8 out of 10 stars for the Android version and wrote that Vector ' s playability makes up for its lack of innovation. [1] In their review of the iOS version, Slide to Play wrote "Vector is a fantastic free-running simulation with plenty to love", though the reviewer described the gameplay as "a bit repetitive at times". [2]

  3. Levinson recursion - Wikipedia

    en.wikipedia.org/wiki/Levinson_recursion

    Levinson recursion or Levinson–Durbin recursion is a procedure in linear algebra to recursively calculate the solution to an equation involving a Toeplitz matrix.The algorithm runs in Θ(n 2) time, which is a strong improvement over Gauss–Jordan elimination, which runs in Θ(n 3).

  4. Vector algebra - Wikipedia

    en.wikipedia.org/wiki/Vector_algebra

    In mathematics, vector algebra may mean: The operations of vector addition and scalar multiplication of a vector space; The algebraic operations in vector calculus (vector analysis) – including the dot and cross products of 3-dimensional Euclidean space; Algebra over a field – a vector space equipped with a bilinear product

  5. Equation solving - Wikipedia

    en.wikipedia.org/wiki/Equation_solving

    An example of using Newton–Raphson method to solve numerically the equation f(x) = 0. In mathematics, to solve an equation is to find its solutions, which are the values (numbers, functions, sets, etc.) that fulfill the condition stated by the equation, consisting generally of two expressions related by an equals sign.

  6. Vector (mathematics and physics) - Wikipedia

    en.wikipedia.org/wiki/Vector_(mathematics_and...

    In mathematics and physics, a vector space (also called a linear space) is a set whose elements, often called vectors, can be added together and multiplied ("scaled") by numbers called scalars. The operations of vector addition and scalar multiplication must satisfy certain requirements, called vector axioms .

  7. Runge–Kutta methods - Wikipedia

    en.wikipedia.org/wiki/Runge–Kutta_methods

    The consequence of this difference is that at every step, a system of algebraic equations has to be solved. This increases the computational cost considerably. If a method with s stages is used to solve a differential equation with m components, then the system of algebraic equations has ms components.

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