首页|Exploring reservoir computing:Implementation via double stochastic nanowire networks

Exploring reservoir computing:Implementation via double stochastic nanowire networks

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Neuromorphic computing,inspired by the human brain,uses memristor devices for complex tasks.Recent studies show that self-organizing random nanowires can implement neuromorphic information processing,enabling data analysis.This paper presents a model based on these nanowire networks,with an improved conductance variation profile.We sug-gest using these networks for temporal information processing via a reservoir computing scheme and propose an efficient data encoding method using voltage pulses.The nanowire network layer generates dynamic behaviors for pulse voltages,allowing time series prediction analysis.Our experiment uses a double stochastic nanowire network architecture for pro-cessing multiple input signals,outperforming traditional reservoir computing in terms of fewer nodes,enriched dynamics and improved prediction accuracy.Experimental results confirm the high accuracy of this architecture on multiple real-time series datasets,making neuromorphic nanowire networks promising for physical implementation of reservoir computing.

double-layer stochastic(DS)nanowire network architectureneuromorphic computationnanowire networkreservoir computingtime series prediction

唐健峰、夏磊、李广隶、付军、段书凯、王丽丹

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College of Artificial Intelligence,Southwest University,Chongqing 400715,China

State Key Laboratory of Intelligent Vehicle Safety Technology,Chongqing 400715,China

National & Local Joint Engineering Laboratory of Intelligent Transmission and Control Technology,Chongqing 400715,China

Chongqing Brain Science Collaborative Innovation Center,Chongqing 400715,China

Brain-inspired Computing & Intelligent Control of Chongqing Key Laboratory,Chongqing 400715,China

Key Laboratory of Luminescence Analysis and Molecular Sensing,Ministry of Education,Southwest University,Chongqing 400715,China

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国家自然科学基金国家自然科学基金国家自然科学基金Chongqing Talent Plan"Contract System"ProjectNational Key Laboratory of Smart Vehicle Safety Technology Open Fund ProjectChongqing Technology Innovation and Application Development Special Major ProjectCollege of Artificial Intelligence,Southwest University,and State Key Laboratory of Intelligent Vehicle Safety Technology

U20A202276207620862076207CQYC20210302257IVSTSKL-202309CSTB2023TIAD-STX0020

2024

10.1088/1674-1056/aceeea

中国物理B(英文版)
中国物理学会和中国科学院物理研究所

中国物理B(英文版)

CSTPCDEI
影响因子：0.995
ISSN：1674-1056
年,卷(期)：2024.33(3)
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