DOI: https://doi.org/10.29363/nanoge.neuronics.2024.005
Publication date: 18th December 2023
Neuromorphic sensing and computing exploits signal encoding and computing inspired by biological brains, down to spiking signal representation. Brain efficiency is overwhelming. the human brain consumes about 20W of power but is capable of remarkably sophisticated cognitive tasks with very low latencies. The visual system, for example, can explore highly complex scenes and be able to detect specific objects, partially occluded, and quite quickly. In this presentation, we will show event cameras that mimic biological retinae. They do not generate frame sequences but provide a flow of continuous spikes (which we call events), each with a pixel coordinate, that represent the dynamic changes in a visual scene. These address events become available with sub-microsecond latency and can be processed by a spiking neural neural immediately. This way, a compound system with an event camera and a hardware spiking neural network can perform object recognition with sub-millisecond latency. For the spiking processing, we will show chips that exploit nanoscale memristor devices as synaptic devices.
This work has been partly funded by EU grants 824164, 871371, 899559, 101070908, 101070679.
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