于洪洁 张文龙 童伟君

中文摘要:
      目的 研究单个Hindmarsh-Rose(H-R)神经元模型从周期动力学模式转向混沌模式的自适应反控制问题。 方法 利用施加正弦函数延迟自反馈方法进行数值模拟分析，分别将耦合强度和时间延迟作为控制参数。结果 通过大量的数值模拟计算，给出神经元的膜电位变量随耦合强度和时间延迟两个参数变化的分岔图，发现在耦合强度值和时间延迟两个参数组合的一些范围内，本来是3峰周期动力学模式的H-R神经元运动可被反控制成混沌模式及其他周期模式的运动。结论 对H-R神经进行反控制的正弦延迟自适应反馈法是有效的，耦合强度和时间延迟均为反控制的重要参数。控制过程反映了神经独有的自适应的信息识别的动力学特性。
英文摘要:
      Objective To study the self-adaptive anti-control of a single H-R neuronal system transformed from periodic dynamics pattern to chaos. Methods Numerical analysis was performed by adding sine function self-delay feedback while coupling intensity and time-delay, respectively, as the control parameters. Results By numerical simulation and analysis, it was found that in a certain range of the combination of coupling intensity and time-delay, the time-interval sequences of the dynamical pattern of a single H-R neuronal system could be controlled from a periodical pattern of 3 spikes onto chaos and other periodical patterns. Conclusions The method of self-adaptive feedback of sine function is effective for the anti-control of H-R neuron, and the coupling intensity and time-delay are both important parameters. The particular self-adaptive dynamics of information identification to neuron is reflected in the control process.