Neuromorphic Control
This work addresses the problem of designing and controlling neuromorphic systems for computing, sensing, and actuation, but it appears incremental as it builds on existing biological principles without claiming major breakthroughs.
The paper tackled the need for new control paradigms in neuromorphic systems by introducing a mixed-feedback organization inspired by biological neurons, resulting in a simple control methodology that reframes neuronal control as an input-output shaping problem and demonstrates scalability in elementary network examples.
Neuromorphic engineering is a rapidly developing field that aims to take inspiration from the biological organization of neural systems to develop novel technology for computing, sensing, and actuating. The unique properties of such systems call for new signal processing and control paradigms. The article introduces the mixed feedback organization of excitable neuronal systems, consisting of interlocked positive and negative feedback loops acting in distinct timescales. The principles of biological neuromodulation suggest a methodology for designing and controlling mixed-feedback systems neuromorphically. The proposed design consists of a parallel interconnection of elementary circuit elements that mirrors the organization of biological neurons and utilizes the hardware components of neuromorphic electronic circuits. The interconnection structure endows the neuromorphic systems with a simple control methodology that reframes the neuronal control as an input-output shaping problem. The potential of neuronal control is illustrated on elementary network examples that suggest the scalability of the mixed-feedback principles.