Wang Sheng-Jun, Xu Xin-Jian, Wu Zhi-Xi, Wang Ying-Hai
Institute of Theoretical Physics, Lanzhou University, Lanzhou Gansu 730000, China.
Phys Rev E Stat Nonlin Soft Matter Phys. 2006 Oct;74(4 Pt 1):041915. doi: 10.1103/PhysRevE.74.041915. Epub 2006 Oct 25.
We study the effects of the degree distribution in mutual synchronization of two-layer neural networks. We carry out three coupling strategies: large-large coupling, random coupling, and small-small coupling. By computer simulations and analytical methods, we find that couplings between nodes with large degree play an important role in the synchronization. For large-large coupling, less couplings are needed for inducing synchronization for both random and scale-free networks. For random coupling, cutting couplings between nodes with large degree is very efficient for preventing neural systems from synchronization, especially when subnetworks are scale free.
我们研究了两层神经网络相互同步中度数分布的影响。我们实施了三种耦合策略:大-大耦合、随机耦合和小-小耦合。通过计算机模拟和分析方法,我们发现度数大的节点之间的耦合在同步中起着重要作用。对于大-大耦合,无论是随机网络还是无标度网络,诱导同步所需的耦合较少。对于随机耦合,切断度数大的节点之间的耦合对于防止神经系统同步非常有效,特别是当子网络是无标度网络时。