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Physical reservoir computing with emerging electronics
DOI:10.1038/s41928-024-01133-z.png)
Abstract
En 中文
Physical reservoir computing is a form of neuromorphic computing that harvests the dynamic properties of materials for high-efficiency computing. A wide range of physical systems can be used to implement this approach, including electronic, optical and mechanical devices. Electronics can, in particular, provide mixed-signal and fully analogue systems, and could be used to deliver large-scale implementations. Here we examine the development of physical reservoir computing with emerging electronics. We discuss the different architectures, physical nodes, and input and output layers of electrical reservoir computing. We also explore performance benchmarks and the competitiveness of different implementations. Finally, we consider the future development of the technology and highlight challenges that need to be addressed for it to deliver practical applications. This Review examines the development of electrical reservoir computing, considering the architectures, physical nodes, and input and output layers of the approach, as well as performance benchmarks and the competitiveness of different implementations.
Keywords:
REAL-TIME
PERFORMANCE
MEMORY
COMPUTATION
NETWORK
Journal
IF:
40.9
Papers:
1.7K
Citations:
2.1W
Organization
Cited Papers
A memristor-based analogue reservoir computing system for real-time and power-efficient signal processing
NATURE ELECTRONICS
IF40.9
A Unified Framework for Reservoir Computing and Extreme Learning Machines based on a Single Time-delayed Neuron
SCIENTIFIC REPORTS
IF3.9
Multilayer Reservoir Computing Based on Ferroelectric α-In2Se3 for Hierarchical Information Processing
ADVANCED MATERIALS
IF26.8

