Spiking Control Systems - Spiking Control Systems: an algorithmic theory for control design of physical event-based systems
From 01-01-2023 to 31-12-2027
Description
Machines compute with bits and clocks, animals compute with spikes and rhythms. The promise of neuromorphic engineering is that we could transform digital technology by imitating the spiking nature of animal computation, combining analog adaptation and digital reliability.
Thirty years after Carver Mead’s initial proposal, event-based cameras have become a technology and neuromorphic computing has become an intense focus both in academia and in industry. Yet, we still lack a proper theory of event-based computation and event-based design. And the very nature of computing with rhythms instead of clocks is still poorly understood.
We propose that the spike is a consequence of analog computing with mixed (that is, positive and negative) feedback. We will develop a control theory of spiking systems by leveraging the control theory of negative feedback systems to a theory of mixed-feedback systems. The mathematical concept of monotonicity provides a modern and unifying foundation for control theory, convex optimisation, and circuit design. Our spiking control theory is grounded in mixed-monotonicity. It is algorithmic because it leverages the methodology of convex optimisation, and it is physical because it leverages the interconnection methodology of circuit theory.
A central objective of the proposed research is a novel event-based internal model principle of significance both for control theory and for neuroscience. We will investigate the unique features of event-based online adaptation, and suggest the complementary roles of inhibition and excitation in novel spiking control sensory networks whose attention and adaptation capabilities can be dynamically modulated.
Ultimately, this proposal aims at novel design principles for physical devices that could surpass the learning and adaptation capabilities of current digital machines, advancing the promise of neuromorphic engineering.
Team
- Rodolphe Sepulchre, Grantee
Financing
Funding: ERC - European Research Council
Program/Grant Type: ERC Adv - ERC Adv
Events
2/09/2024:
PhD defense - Martijn Oldenhof
Machine Learning for Advanced Chemical Analysis and Structure Recognition in Drug Discovery
3/09/2024:
Meet the Jury Igor Tetko on Advanced Machine Learning in Drug Discovery
12/09/2024:
Multimodal analysis of cell-free DNA for sensitive cancer detection in low-coverage and low-sample settings
Seminar by Antoine Passemiers
News
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Joos Vandewalle is nieuwe voorzitter KVAB
09 October 2016
Op 5 oktober 2016 heeft de Algemene Vergadering van de Academie KVAB Joos Vandewalle verkozen tot voorzitter van de KVAB.