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Bio-Inspired Neuromorphic Sensory Systems from Intelligent Perception to Nervetronics
Elvis K Boahen1, Hyukmin Kweon1,2, Hayoung Oh1
1Department of Chemical Engineering, Hanyang University, Seoul, 04763, Republic of Korea.
Advanced Science (Weinheim, Baden-Wurttemberg, Germany)
|November 11, 2024
Summary
Neuromorphic artificial sensory systems mimic the human nervous system for advanced AI. This review explores synaptic devices and neural networks, crucial for brain-like computing in robotics and wearables.
Area of Science:
- Neuroscience
- Computer Science
- Materials Science
Background:
- Neuromorphic artificial sensory systems are inspired by the human nervous system's signal processing.
- These systems integrate sensory synaptic devices and neural network algorithms for brain-like computing.
- Applications include humanoid robotics, prosthetics, and wearable technologies.
Purpose of the Study:
- To review the relationship between synaptic device technologies and neural network processing algorithms.
- To highlight their mutual influence on artificial intelligence (AI) capabilities.
- To explore advancements in artificial synaptic properties and their processing through artificial neural networks (ANNs).
Main Methods:
- Review of current literature on synaptic device technologies and ANNs.
- Analysis of artificial synaptic properties triggered by various stimuli (optical, auditory, mechanical, chemical).
- Examination of ANN processing for applications like image and multimodal pattern recognition.
Main Results:
- Advancements in artificial synaptic properties responding to diverse stimuli.
- Successful application of ANNs for processing sensory inputs in image and multimodal pattern recognition.
- Demonstration of artificial synapse emulation of biological perception.
Conclusions:
- The integration of synaptic devices and neural networks is key to neuromorphic systems.
- Further understanding of neural network processing is essential for innovation in this field.
- Future development requires addressing challenges in refining these complex brain-like computing systems.
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