A key strength of the toolkit formed by CellNOptR, CNORdt, CNORode and CNORfuzzy is that it covers multiple logic modeling formalisms (Boolean steady-state, Boolean multiple steady-state, Boolean time courses through synchronous update, steady-state constrained fuzzy logic and continuous logic-based ODEs).
While limit cycles are dependent upon the choice of updating scheme, steady state attractors are uniform across dynamic schemes; their stabilization, therefore, requires comparatively less information concerning system dynamics.
Furthermore, the update rule affects the steady state solution.
These functions have the ability to depict the changes in the temporal profile of wind speeds with space and can be added to the earlier empirical and analytical steady state models to update them from steady state to unsteady state "time dependent" simulation.
We define various statistically equivalent codon-based simulation algorithms and analyze the importance of the update rule in determining the steady state, an aspect often neglected.
The update rate provided by the balanced steady state free precession (b-SSFP or TrueFISP) radial k-space interactive pulse sequence (IRTTT, Siemens Medical Solutions, Erlangen, Germany) is of the order of 300 ms, and spatial resolution of 1.6 × 1.6 mm.
For simulation, we use a synchronous updating scheme until all nodes have reached a steady state.
We apply the ROA update scheme to the network of Figure 1(a), and show) that it has two steady state attractors that coincide with the steady states under synchronous update).
This marks the importance of the update rule in the sense that it determines the unique steady state solution given the event rates.
Hence, given the event rates, which unique steady state solution is finally determined is made by the update rule.
A comparison of the steady state solutions caused by the random-sequential and parallel update rules respectively, is provided in Figure 3.
