![]() ![]() ![]() Weĭeveloped a simple way of quantifying this classification: we considerĬA with an extremely low number of cells, consider all possible initialĬonditions, and quantify by the number of final modes with periods larger Systems accounting both for their flexibility and their reliability. "edge of chaos" and is believed to play an essential role in biological In general, CA can lead to four different modes: i) homogeneity ("classġ") ii) periodicity ("class 2") iii) chaos ("class 3") and iv) an erraticĪlternation of periodicity and chaos ("class 4"). Which is usually medicated by a total heart depolarization that permits This causes an abnormally fast heart beat (tachycardia), Such a region may appear in scars after an infarct. They emerge from the sinus node (point at t=0) and theyīreak at a region of transitory lower repolarization rate (rectangle t=0). The simulation example shown below is that of depolarizing waves in Used for quantitative analyses that require well-defined curvatures, e.g. Spatial discretization (shown below circular neighbourhood with radius To avoid this, we used a quasi-stochastic The state of a spatial cell at a given time step is determinedīy the states in a neighbourhood of that cell at the previous time step,Ī drawback in CA has been that the shape of the simulated spatial structuresĭepends on the shape of the cells. The computing time is, in general, lower than using partial differentialĬA are descriptions of phenomena that are discrete in time, in spaceĪnd in states. They are usually fast and easy to programm. Cellular automata (CA) are descriptions of dynamic phenomena thatĭo not use equations but rules, like in a game. ![]()
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