异步随机更新下随机布尔网络的吸引子和盆熵
Attractor and Basin Entropies of Random Boolean Networks Under Asynchronous Stochastic Update
摘要：
本文介绍了一种研究具有异步随机更新的随机布尔网络的数值方法。状态网络中的每个节点以相等的占用概率开始，然后该概率分布演变为稳定状态。节点的有限占据概率决定了吸引子和吸引盆的大小。对于同步更新，只有在临界网络中，系统吸引子长度服从幂律分布时，流域熵才随系统规模的增大而增大。我们确定的吸引子和盆地大小的冻结网络的连通性K = 1的数量的分布解析。
英文摘要：
We introduce a numerical method to study random Boolean networks with asynchronous stochas- tic update. Each node in the network of states starts with equal occupation probability and this probability distribution then evolves to a steady state. Nodes left with finite occupation probability determine the attractors and the sizes of their basins. As for synchronous update, the basin entropy grows with system size only for critical networks, where the distribution of attractor lengths is a power law. We determine analytically the distribution for the number of attractors and basin sizes for frozen networks with connectivity K = 1.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
