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  2. Riemann sum - Wikipedia

    en.wikipedia.org/wiki/Riemann_sum

    Left and right methods make the approximation using the right and left endpoints of each subinterval, respectively. Upper and lower methods make the approximation using the largest and smallest endpoint values of each subinterval, respectively. The values of the sums converge as the subintervals halve from top-left to bottom-right.

  3. Riemann integral - Wikipedia

    en.wikipedia.org/wiki/Riemann_integral

    One popular restriction is the use of "left-hand" and "right-hand" Riemann sums. In a left-hand Riemann sum, t i = x i for all i, and in a right-hand Riemann sum, t i = x i + 1 for all i. Alone this restriction does not impose a problem: we can refine any partition in a way that makes it a left-hand or right-hand sum by subdividing it at each t i.

  4. Numerical integration - Wikipedia

    en.wikipedia.org/wiki/Numerical_integration

    A quadrature rule is an approximation of the definite integral of a function, usually stated as a weighted sum of function values at specified points within the domain of integration. Numerical integration methods can generally be described as combining evaluations of the integrand to get an approximation to the integral.

  5. Euler method - Wikipedia

    en.wikipedia.org/wiki/Euler_method

    For this reason, the Euler method is said to be a first-order method, while the midpoint method is second order. We can extrapolate from the above table that the step size needed to get an answer that is correct to three decimal places is approximately 0.00001, meaning that we need 400,000 steps.

  6. Backward Euler method - Wikipedia

    en.wikipedia.org/wiki/Backward_Euler_method

    The backward Euler method is an implicit method: the new approximation + appears on both sides of the equation, and thus the method needs to solve an algebraic equation for the unknown +. For non- stiff problems, this can be done with fixed-point iteration :

  7. Calculus of variations - Wikipedia

    en.wikipedia.org/wiki/Calculus_of_Variations

    The calculus of variations began with the work of Isaac Newton, such as with Newton's minimal resistance problem, which he formulated and solved in 1685, and published in his Principia in 1687, [2] which was the first problem in the field to be clearly formulated and correctly solved, and was one of the most difficult problems tackled by variational methods prior to the twentieth century.

  8. Euler–Maclaurin formula - Wikipedia

    en.wikipedia.org/wiki/Euler–Maclaurin_formula

    In mathematics, the Euler–Maclaurin formula is a formula for the difference between an integral and a closely related sum. It can be used to approximate integrals by finite sums, or conversely to evaluate finite sums and infinite series using integrals and the machinery of calculus .

  9. Euler–Lagrange equation - Wikipedia

    en.wikipedia.org/wiki/Euler–Lagrange_equation

    The left hand side of the previous equation is the functional derivative / of the functional . A necessary condition for a differentiable functional to have an extremum on some function is that its functional derivative at that function vanishes, which is granted by the last equation.