Daten zum Projekt

Neuromorphic Sensing with Active Efficient Coding for Edge Computing

Initiative: NEXT
Ausschreibung: Neuromorphic Computing
Bewilligung: 10.07.2023
Laufzeit: 4 Jahre


Neuromorphic Sensing with Active Efficient Coding for Edge Computing (SNACE) Edge-computing applications (e.g., medical devices, wearable electronics, or mobile robotic platforms) typically require processing various sensory signals with constrained computing power. The current state-of-the-art technology in Integrated Circuits (ICs) has already witnessed tremendous progress towards more energy-efficient solutions for edge computing, with higher scores achieved with neuromorphic mixed-signal and analog subthreshold architectures at large scales. However, efficient deployment of such systems in real-world scenarios imposes the need for more robust and reliable front-end designs that can cope with external noise and device variability. As proposed by the Active Efficient Coding (AEC) theory, it appears that biological systems have learned to cope with finite computational resources and environment complexity by compensating with adaptive behavior. Hence, if applied to edge computing, such principles promise to solve current roadblocks towards truly efficient sensory systems on the edge. Thus, the goal of this project is to unleash the potential of extreme-edge computing by leveraging the principles of AEC for efficient near/in-sensor modulation. We will provide a framework for designing and characterizing a novel generation of Adaptive Neuromorphic Sensory (ANS) systems that can jointly extract sensory information from multiple sources while modulating sensor transduction. Upon quantitative assessment of the ACE theory applied to embedded systems, we propose to deliver and validate an example ANS system in a real-world scenario.


  • Dr.-Ing. René Schuster

    Rheinland-Pfälzische Technische
    Universität Kaiserslautern-Landau (RPTU)
    Computer Science
    Augmented Vision

  • Dr. Siao Wang, Ph.D.

    Italian Institute of Technology (IIT)
    Center for Robotics and Intelligent Systems
    Event Driven Perception for Robotics

  • Lea Steffen

    FZI Forschungszentrum Informatik
    am Karlsruher Institut für Technologie
    Interaktive Diagnose- und Servicesysteme

  • Dr. Nicoletta Risi, Ph.D

    University of Groningen
    Faculty of Science and Engineering
    Zernike Institute for Advanced Materials

  • Dr. Claudia Lenk

    Technische Universität Ilmenau
    Fakultät Elektro- und Informationstechnik
    Institut für Mikro- und Nano-Elektronik