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研究了具有时滞的分数阶复值神经网络的分岔控制问题。通过对原系统设计反馈控制器，调节反馈增益参数来改善系统的动态性能，并产生Hopf分岔；给出了系统产生Hopf分岔的充分条件和临界参数值；最后通过数值仿真验证了理论结果的正确性。
Abstract：This study investigates the bifurcation control problem of fractional complex-valued neural networks with time delays. By designing a feedback controller for the original system and adjusting the feedback gain parameters,the dynamic performance of the system is improved, and a Hopf bifurcation is generated. The sufficient conditions for the system to exhibit Hopf bifurcation and the critical parameter values are provided. Finally, the theoretical results is verified through numerical simulations.
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基本信息:
DOI：10.12194/j.ntu.20221128004
中图分类号:TP183
引用信息:
[1]宋倩倩,程尊水.基于反馈控制的分数阶复值神经网络的Hopf分岔[J],2023,22(03):56-71+94.DOI:10.12194/j.ntu.20221128004.
基金信息:
国家自然科学基金面上项目（61374011）;; 山东省自然科学基金面上项目（ZR2020MF080）