
Spikes and rhythms organize control and communication in the animal world, in contrast to the bits and clocks of digital technology. As continuous-time signals that can be counted, spikes have a mixed nature. This paper reviews ongoing efforts to develop a control theory of spiking systems. The central thesis is that the mixed nature of spiking results from a mixed feedback principle, and that a control theory of mixed feedback can be grounded in the operator theoretic concept of maximal monotonicity. As a nonlinear generalization of passivity, maximal monotonicity acknowledges at once the physics of electrical circuits, the algorithmic tractability of convex optimization, and the feedback control theory of incremental passivity. We discuss the relevance of a theory of spiking control systems in the emerging age of event-based technology.
Control systems, Convex functions, Biological system modeling, Resistors, Systems and Control (eess.SY), passive and active electrical circuits, Electrical Engineering and Systems Science - Systems and Control, Automata, feedback control, neuroscience, Integrated circuit modeling, Control theory, FOS: Electrical engineering, electronic engineering, information engineering, Event-based control
Control systems, Convex functions, Biological system modeling, Resistors, Systems and Control (eess.SY), passive and active electrical circuits, Electrical Engineering and Systems Science - Systems and Control, Automata, feedback control, neuroscience, Integrated circuit modeling, Control theory, FOS: Electrical engineering, electronic engineering, information engineering, Event-based control
| citations 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). | 10 | |
| 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. | Top 10% | |
| 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. | Top 10% |
