Research topic: neuromorphic engineering systems and applications. A snapshot of neuromorphic systems engineering

Delbrück, Tobi; Schaik, André van; Hasler, Jennifer

doi:10.3389/fnins.2014.00424

Cited by 3 publications

(1 citation statement)

References 14 publications

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“…Because of these, biological neural systems are more efficient and faster than any hardware/software computing platforms can accomplish for the given scale ( Lohman, 1989 ; Picard et al, 2001 ). As the solution for efficient processing of enormous dataset sizes, electrical implementation of neural systems has been an important approach for external information acquisition (e.g., sensor), and more significantly, the external information processing and execution through cognitive processes (e.g., neuromorphic computing systems) ( Delbruck et al, 2014 ). Artificial synapses can control information flow, data processing and memory function by modulating the synaptic weight ( Voglis and Tavernarakis, 2006 ; Gkoupidenis et al, 2015 ).…”

Section: Introductionmentioning

confidence: 99%

Neuromorphic Devices for Bionic Sensing and Perception

Zeng

Zhang

et al. 2021

Front. Neurosci.

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Neuromorphic devices that can emulate the bionic sensory and perceptual functions of neural systems have great applications in personal healthcare monitoring, neuro-prosthetics, and human–machine interfaces. In order to realize bionic sensing and perception, it’s crucial to prepare neuromorphic devices with the function of perceiving environment in real-time. Up to now, lots of efforts have been made in the incorporation of the bio-inspired sensing and neuromorphic engineering in the booming artificial intelligence industry. In this review, we first introduce neuromorphic devices based on diverse materials and mechanisms. Then we summarize the progress made in the emulation of biological sensing and perception systems. Finally, the challenges and opportunities in these fields are also discussed.

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