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  2. Weak formulation - Wikipedia

    en.wikipedia.org/wiki/Weak_formulation

    In a weak formulation, equations or conditions are no longer required to hold absolutely (and this is not even well defined) and has instead weak solutions only with respect to certain "test vectors" or "test functions". In a strong formulation, the solution space is constructed such that these equations or conditions are already fulfilled.

  3. Weak solution - Wikipedia

    en.wikipedia.org/wiki/Weak_solution

    In mathematics, a weak solution (also called a generalized solution) to an ordinary or partial differential equation is a function for which the derivatives may not all exist but which is nonetheless deemed to satisfy the equation in some precisely defined sense. There are many different definitions of weak solution, appropriate for different ...

  4. Tsirelson's stochastic differential equation - Wikipedia

    en.wikipedia.org/wiki/Tsirelson's_stochastic...

    Tsirelson's stochastic differential equation (also Tsirelson's drift or Tsirelson's equation) is a stochastic differential equation which has a weak solution but no strong solution. It is therefore a counter-example and named after its discoverer Boris Tsirelson. [1] Tsirelson's equation is of the form

  5. Uncertainty avoidance - Wikipedia

    en.wikipedia.org/wiki/Uncertainty_avoidance

    In cross-cultural psychology, uncertainty avoidance is how cultures differ on the amount of tolerance they have of unpredictability. [1] Uncertainty avoidance is one of five key qualities or dimensions measured by the researchers who developed the Hofstede model of cultural dimensions to quantify cultural differences across international lines and better understand why some ideas and business ...

  6. Stochastic differential equation - Wikipedia

    en.wikipedia.org/wiki/Stochastic_differential...

    A weak solution consists of a probability space and a process that satisfies the integral equation, while a strong solution is a process that satisfies the equation and is defined on a given probability space. The Yamada–Watanabe theorem makes a connection between the two. An important example is the equation for geometric Brownian motion

  7. Sensitivity analysis - Wikipedia

    en.wikipedia.org/wiki/Sensitivity_analysis

    Taking into account uncertainty arising from different sources, whether in the context of uncertainty analysis or sensitivity analysis (for calculating sensitivity indices), requires multiple samples of the uncertain parameters and, consequently, running the model (evaluating the -function) multiple times. Depending on the complexity of the ...

  8. Calculus of variations - Wikipedia

    en.wikipedia.org/wiki/Calculus_of_Variations

    A simple example of such a problem is to find the curve of shortest length connecting two points. If there are no constraints, the solution is a straight line between the points. However, if the curve is constrained to lie on a surface in space, then the solution is less obvious, and possibly many solutions may exist.

  9. Galerkin method - Wikipedia

    en.wikipedia.org/wiki/Galerkin_method

    Ritz–Galerkin method (after Walther Ritz) typically assumes symmetric and positive definite bilinear form in the weak formulation, where the differential equation for a physical system can be formulated via minimization of a quadratic function representing the system energy and the approximate solution is a linear combination of the given set ...

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