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  2. Linear multistep method - Wikipedia

    en.wikipedia.org/wiki/Linear_multistep_method

    The first Dahlquist barrier states that a zero-stable and linear q-step multistep method cannot attain an order of convergence greater than q + 1 if q is odd and greater than q + 2 if q is even. If the method is also explicit, then it cannot attain an order greater than q ( Hairer, Nørsett & Wanner 1993 , Thm III.3.5).

  3. Zero stability - Wikipedia

    en.wikipedia.org/wiki/Zero_stability

    A linear multistep method is zero-stable if all roots of the characteristic equation that arises on applying the method to ′ = have magnitude less than or equal to unity, and that all roots with unit magnitude are simple. [2]

  4. Truncation error (numerical integration) - Wikipedia

    en.wikipedia.org/wiki/Truncation_error...

    For linear multistep methods, an additional concept called zero-stability is needed to explain the relation between local and global truncation errors. Linear multistep methods that satisfy the condition of zero-stability have the same relation between local and global errors as one-step methods.

  5. Numerical methods for ordinary differential equations - Wikipedia

    en.wikipedia.org/wiki/Numerical_methods_for...

    Explicit examples from the linear multistep family include the Adams–Bashforth methods, and any Runge–Kutta method with a lower diagonal Butcher tableau is explicit. A loose rule of thumb dictates that stiff differential equations require the use of implicit schemes, whereas non-stiff problems can be solved more efficiently with explicit ...

  6. Stiff equation - Wikipedia

    en.wikipedia.org/wiki/Stiff_equation

    Explicit multistep methods can never be A-stable, just like explicit Runge–Kutta methods. Implicit multistep methods can only be A-stable if their order is at most 2. The latter result is known as the second Dahlquist barrier; it restricts the usefulness of linear multistep methods for stiff equations. An example of a second-order A-stable ...

  7. Trapezoidal rule (differential equations) - Wikipedia

    en.wikipedia.org/wiki/Trapezoidal_rule...

    In numerical analysis and scientific computing, the trapezoidal rule is a numerical method to solve ordinary differential equations derived from the trapezoidal rule for computing integrals. The trapezoidal rule is an implicit second-order method, which can be considered as both a Runge–Kutta method and a linear multistep method.

  8. Runge–Kutta methods - Wikipedia

    en.wikipedia.org/wiki/Runge–Kutta_methods

    Dahlquist (1963) proposed the investigation of stability of numerical schemes when applied to nonlinear systems that satisfy a monotonicity condition. The corresponding concepts were defined as G-stability for multistep methods (and the related one-leg methods) and B-stability (Butcher, 1975) for Runge–Kutta

  9. Talk:Linear multistep method - Wikipedia

    en.wikipedia.org/wiki/Talk:Linear_multistep_method

    1 Dahlquist Barriers. 1 comment. 2 AB coefficients. 1 comment. 3 It's correct. 4 Function of one variable or two? 1 comment. 5 Stability and A-stability. 2 comments.