
arXiv: 2401.04324
The theory of mixed-feedback systems provides an effective framework for the design of robust and tunable oscillations in nonlinear systems characterized by interleaved fast positive and slow negative feedback loops. The goal of this paper is to extend the mixed-feedback oscillation design framework to networks. To this aim, we introduce a network model of coupled mixed-feedback systems, ask under which conditions it exhibits a collective oscillatory rhythm, and if, and how, this rhythm can be shaped by network design. In the proposed network model, node dynamics are nonlinear and defined by a tractable realization of the mixed-feedback structure. Coupling between nodes is also nonlinear and defined by a tractable abstraction of synaptic coupling between neurons. We derive constructive conditions under which the spectral properties of the network adjacency matrix fully and explicitly determine both the emergence of a stable network rhythm and its detailed rhythmic profile, i.e., the pattern of relative oscillation amplitudes and phase differences. Our theoretical developments are grounded on ideas from dominant systems and bifurcation theory. They provide a new framework for the analysis and design of nonlinear network rhythms.
20 pages, 6 figures
Optimization and Control (math.OC), FOS: Mathematics, FOS: Physical sciences, Dynamical Systems (math.DS), Mathematics - Dynamical Systems, Mathematics - Optimization and Control, Adaptation and Self-Organizing Systems (nlin.AO), Nonlinear Sciences - Adaptation and Self-Organizing Systems
Optimization and Control (math.OC), FOS: Mathematics, FOS: Physical sciences, Dynamical Systems (math.DS), Mathematics - Dynamical Systems, Mathematics - Optimization and Control, Adaptation and Self-Organizing Systems (nlin.AO), Nonlinear Sciences - Adaptation and Self-Organizing Systems
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 1 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
