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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. 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 ...

  5. Richard Shiffrin - Wikipedia

    en.wikipedia.org/wiki/Richard_Shiffrin

    This model quantified the nature of retrieval from long-term memory and characterized recall as a memory search with cycles of sampling and recovery. [8] In 1984, another quantum step forward occurred, when the theory was extended to recognition memory, in which a decision is based on summed activation of related memory traces. [ 9 ]

  6. Germund Dahlquist - Wikipedia

    en.wikipedia.org/wiki/Germund_Dahlquist

    Germund Dahlquist (16 January 1925 – 8 February 2005) was a Swedish mathematician known primarily for his early contributions to the theory of numerical analysis as applied to differential equations.

  7. General linear methods - Wikipedia

    en.wikipedia.org/wiki/General_linear_methods

    General linear methods (GLMs) are a large class of numerical methods used to obtain numerical solutions to ordinary differential equations. They include multistage Runge–Kutta methods that use intermediate collocation points , as well as linear multistep methods that save a finite time history of the solution.

  8. Multigrid method - Wikipedia

    en.wikipedia.org/wiki/Multigrid_method

    (More generally, coarse grid unknowns can be particular linear combinations of fine grid unknowns.) Thus, AMG methods become black-box solvers for certain classes of sparse matrices . AMG is regarded as advantageous mainly where geometric multigrid is too difficult to apply, [ 20 ] but is often used simply because it avoids the coding necessary ...

  9. Atkinson–Shiffrin memory model - Wikipedia

    en.wikipedia.org/wiki/Atkinson–Shiffrin_memory...

    The Atkinson–Shiffrin model (also known as the multi-store model or modal model) is a model of memory proposed in 1968 by Richard Atkinson and Richard Shiffrin. [1] The model asserts that human memory has three separate components: a sensory register, where sensory information enters memory,