Neuromorphic Processing Systems

The term neuromorphic refers to electronic devices, circuits, and systems that implement the same basic operations as those the nervous system uses, and that use the same organizing principles used by the nervous system.

Neuromorphic engineering is an interdisciplinary field that feeds from biology (neuroscience), physics (materials science), mathematics (graphical networks, belief propagation), computer science (automata, state machines, learning), and engineering (microelectronics and robotics) to develop brain-inspired processing systems.

The aim of this collection is to create a common space for researchers exploring different aspects of neural computation and sensory-motor processing.

A non-exhaustive list of topics includes:

• Spiking Neural Networks.
• Recurrent Neural Networks.
• Learning and Plasticity.
• Neuromorphic sensors.
• Multi-core neuromorphic processors.
• Hybrid memristive/CMOS neuromorphic systems.
• Co-designed software-hardware architectures.
• Event-based processing and applications.

Collection advisors: Giacomo Indiveri (University of Zurich, Switzerland)