AI & ML
Describing Functions and Phase Response Curves of Excitable Systems
arXiv cs.SY0 views
arXiv:2511.16235v4 Announce Type: replace Abstract: The describing function (DF) and phase response curve (PRC) are classical tools for the analysis of feedback oscillations and rhythmic behaviors, widely used across control engineering, biology, and neuroscience. These tools are known to have limitations in networks of relaxation oscillators and excitable systems. For this reason, the paper proposes a novel approach tailored to excitable systems. Our analysis focuses on the discrete-event operator mapping input trains of events to output trains of events. The methodology is illustrated on the excitability model of Hodgkin-Huxley. The proposed framework provides a basis for designing and analyzing central pattern generators in networks of excitable neurons, with direct relevance to neuromorphic control and neurophysiology.
Source:https://arxiv.org/abs/2511.16235PreviousMinimum Time Consensus of Multi-agent System under Fuel ConstraintsNextMulti-Agentic AI for Fairness-Aware and Accelerated Multi-modal Large Model Inference in Real-world Mobile Edge Networks
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