One of the promising applications of locally-active memristors (LAMs) is to construct oscillators for oscillatory neural networks. By using two current-controlled (CC) LAMs, a fully CC LAM-based oscillator is designed in this paper. The oscillator principle originates from the small-signal inductive and capacitive impedance characteristics of two different CC LAMs, and thus extra reactance element is not required in the circuit. Based on bifurcation theory and small-signal analysis method, conditions of the equilibrium point instability are quantitatively derived. Theoretical analysis indicates that the circuit oscillation is dependent on three critical parameters. Then, according to the conditions of the equilibrium point instability, parameters design methods of the two LAMs are proposed, including the static and dynamic parameters. A simple NbO_x CC LAM model is taken as an example to conduct detailed simulation analysis. The simulation results verify the feasibility of the proposed circuit and analysis methods. Finally, the effects of the LAM model parameters on the oscillator performance are investigated, which is helpful for optimal design of the oscillator.

局部有源忆阻器（LAM）最有前景的应用之一是构建用于振荡神经网络的振荡器。本文通过使用两个电流控制 (CC) LAM，设计了一种完全基于 CC LAM 的振荡器。振荡器原理源于两种不同CC LAM的小信号感性和容性阻抗特性，因此电路中不需要额外的电抗元件。基于分岔理论和小信号分析方法，定量推导了平衡点不稳定的条件。理论分析表明电路振荡取决于三个关键参数。然后，根据平衡点不稳定的条件，提出了两种LAM的参数设计方法，包括静态参数和动态参数。以简单的NbO _x CC LAM模型为例进行详细的仿真分析。仿真结果验证了所提电路和分析方法的可行性。最后，研究了LAM模型参数对振荡器性能的影响，这有助于振荡器的优化设计。