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We derive an expression for the truncation error resulting from Strang splitting reaction and diffusion operators for an arbitrary number of spatial dimensions, and demonstrate its use in adaptive time step algorithms.
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We restrict the timestep sizes used in the adaptive time integration so that they are not greater than one millisecond, that is, Δ t(max) = 1 msec.
Later, we present experimental results of the sliding window method where we use adaptive time steps in the way described above.
Using locally adaptive time steps in the integration of particle equations, the particles' parameters are updated more frequently in regions of strong gradients than in those of flat gradients, which greatly improves the time efficiency of particle tracing.
For all examples, using equidistant time steps results in longer computation times compared to using adaptive time steps (with an average speed-up factor of 3.5).
By using adaptive time scales, time gradients of signals are extracted to calculate variational directions in an online manner.
They are also robust when used in conjunction with an adaptive time stepping strategy and appear as an interesting alternative to time-splitting pseudo-spectral (TSSP) schemes.
The tricky‐horizon (time‐variant memory size N) algorithm can be used in adaptive filtering [29, 30] and whenever some reference information about the process behavior is available.
The modified Euler method was used to discretise in time and an adaptive time step strategy was employed to ensure stability.
An adaptive time step used in the procedure of acceleration of the simulation.
In ATDNN, adaptive time-delay units are used to capture the temporal relationships between events.
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