Scaling a Mixed-Feedback Approach to Controlling Neuromorphic Circuits

该研究小组利用混合反馈控制理论开发了一种模拟单个神经元行为的神经形态回路。这种电路的新颖之处在于，它的设计和分析可以完全通过塑造电流-电压（I-V）曲线来完成。这种输入输出方法比调整状态空间模型更简单，并且允许对非线性行为进行鲁棒和精确的控制。博士的重点将是设计和表征由多个这样的神经元元素连接在一起的神经形态电路。这些电路有潜在的工程应用，包括电子传感。它们也可以用来模拟和研究生物现象，比如有节奏的神经活动的自发出现。

The research group has used mixed-feedback control theory to develop a neuromorphic circuit mimicking the behaviour of a single neuron. The novelty of this circuit is that its design and analysis can be done purely by shaping the current-voltage (I-V) curves. This input-output approach is simpler than tuning a state-space model, and allows robust and accurate control of non-linear behaviour.The focus of the PhD will be to design and characterise neuromorphic circuits comprising multiple such neuron elements connected together. These circuits potentially have engineering applications, including electronic sensing. They can also be used to model and investigate biological phenomena, such as the spontaneous emergence of rhythmic neural activity.