霍普夫分叉
神经形态工程学
半导体
介电谱
分叉
电阻抗
动力系统理论
生物系统
分岔理论
记忆电阻器
理论(学习稳定性)
控制理论(社会学)
物理
计算机科学
统计物理学
光电子学
人工神经网络
非线性系统
电化学
人工智能
量子力学
电极
机器学习
生物
控制(管理)
摘要
Spontaneous oscillations in a variety of systems, including neurons, electrochemical, and semiconductor devices, occur as a consequence of Hopf bifurcation in which the system makes a sudden transition to an unstable dynamical state by the smooth change of a parameter. We review the linear stability analysis of oscillatory systems that operate by current–voltage control using the method of impedance spectroscopy. Based on a general minimal model that contains a fast-destabilizing variable and a slow stabilizing variable, a set of characteristic frequencies that determine the shape of the spectra and the associated dynamical regimes are derived. We apply this method to several self-sustained rhythmic oscillations in the FitzHugh–Nagumo neuron, the Koper–Sluyters electrocatalytic system, and potentiostatic oscillations of a semiconductor device. There is a deep and physically grounded analogy between different oscillating systems: neurons, electrochemical, and semiconductor devices, as they are controlled by similar fundamental processes unified in the equivalent circuit representation. The unique impedance spectroscopic criteria for widely different variables and materials across several fields provide insight into the dynamical properties and enable the investigation of new systems such as artificial neurons for neuromorphic computation.
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