MemDANCE: Memristor-based Dendritic Analog Computing Enhancement

• Applicants: Professor Dr. Gordon Pipa; Professor Dr. John Paul Strachan
• Subject Area: Electronic Semiconductors, Components and Circuits, Integrated Systems, Sensor Technology, Theoretical Electrical Engineering ; Experimental and Theoretical Network Neuroscience
• Term: since 2023
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 536022217

This project will advance the field of neuromorphic computing in two major directions. First, it will develop memristor-based hardware for extremely energy-efficient spiking recurrent neuronal networks including dendritic computing, a major component of real neuronal systems that is mostly ignored in the field of artificial neuronal networks by today. Secondly, the inclusion of dendritic computing will enable boosting the computational power of spiking recurrent neuronal networks by increasing temporal memory which is necessary for the effective processing of complex temporal sequences including signatures across different temporal scales. Taking both together, this project has the potential for an extremely energy-efficient memristor-based spiking recurrent neuronal network that may be used in edge devices and for hardware-based neuromorphic applications of AI with significantly improved performance.

• DFG Programme: Priority Programmes
• Subproject of: SPP 2262: Memristive Devices Toward Smart Technical Systems
• Co-Investigators: Dr. Farbod Nosrat Nezami; Dr. Ming-Jay Yang