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Consequently, it is reasonable that the cortical model exhibits similar pattern dynamics for those seen in the chemical reaction-diffusion system.
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This is useful both as a means of describing the continuum limits of automata and as an independent foundation for expressing models for pattern dynamics.
We illustrate the power of this approach with convolution-generated motion models for pattern dynamics in developmental biology and excitable media.
The aim of this paper is to introduce SIMULINK modelling for simulating pattern dynamics.
Two network mapping methods are proposed for the analysis and identification of flow pattern dynamics, i.e. Flow Pattern Complex Network (FPCN) and Fluid Dynamic Complex Network (FDCN).
Pattern dynamics research focuses on universal pattern-forming mechanisms for the latter case.
Finally, we examine the Brusselator and cortical model pattern dynamics.
This necessitates monitoring and advance visualisation of spatial patterns of landscape dynamics for evolving appropriate management strategies towards sustainable development approaches.
This study analyses the spatio-temporal pattern of forest cover dynamics for three decades in Falgore Game Reserve in Kano, Nigeria.
This type of combination of the negative and positive feedback loops with a possible diffusible inhibitor is reminiscent of Turing instability dynamics for regular pattern generation [14], although this and other possibilities have not yet been well validated experimentally.
Theoretical explanations for vegetation pattern dynamic emphasized on banded pattern-forming systems on the dynamics of the spot pattern.
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