噪声下耦合网络谐振稳定性迁移预测和控制

This project will focus mainly on the goals to detect the synchronization stability of oscillating collective behaviors in network, to predict and control the instability of the network synchronization and pattern formation. The focuses of the research work are to construct networks with different types of topology, which the local kinetics is described by resonance circuit or nonlinear oscillators, predictive control and noise suppression can be carried on these network so that the synchronization instability can be prevented. The contents to be investigated are considered as follows. 1)A feasible and reliable neuronal circuit is designed by using memristive device (memristor) and sensitive inductor (Josephson junction) with the ion channel effect involved, furthermore, the stability and series analysis will be carried out on electronic emulation software and FPGA. 2) Desynchronization induced by collapse in electric device between finite neuronal circuits under coupling is discussed, furthermore, desynchronization and pattern instability in one-layer network are investigated in presence of stochastic diffusive collapse. 3)A cascading collapse on two-layer and multi-layer network is considered to predict and detect the instability of network. 4) Pattern selection, control and diffusive collapse on network with noise being considered. The project could give some important results on information to predictive control of network synchronization, pattern stability and emergence of neuronal diseases.

本项目拟利用斑图动力学理论和复杂网络方法预测网络群体振荡行为的稳定性，开展控制网络同步和斑图失稳问题的研究。工作重点是通过多种谐振电路和振子耦合来构造不同拓扑结构的网络,实现对谐振网络稳定性预测控制和去噪控制,有效地预防同步失稳。课题内容包含：1)利用灵敏电感元件约瑟夫森结、记忆效应的忆阻器等设计神经元电路并考虑离子通道效应和噪声效应;通过电子仿真软件和FPGA进一步测试稳定性。2）有限个神经元电路耦合下核心电路元件崩溃诱发的去同步，单层多节点网络随机扩散性崩溃诱发的网络去同步和斑图失稳。3)双层和多层网络中级联崩溃诱发的网络同步失稳和预测。4)噪声驱动下网络斑图诱发和崩溃扩散问题。通过本项目的研究将为神经元电路网络同步稳定性控制和神经性疾病涌现提供重要参考信息。