检索结果-南通市图书馆

Exploring reservoir computing:Implementation via double stochastic nanowire networks

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Chinese Physics B 2024年第3期33卷 572-582页

作者：唐健峰夏磊李广隶付军段书凯王丽丹 College of Artificial Intelligence Southwest UniversityChongqing 400715China Brain-inspired Computing & Intelligent Control of Chongqing Key Laboratory Chongqing 400715China National & Local Joint Engineering Laboratory of Intelligent Transmission and Control Technology Chongqing 400715China Chongqing Brain Science Collaborative Innovation Center Chongqing 400715China Key Laboratory of Luminescence Analysis and Molecular Sensing Ministry of EducationSouthwest UniversityChongqing 400715China State Key Laboratory of Intelligent Vehicle Safety Technology Chongqing 400715China

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 suggest 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 processing 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.

关键词： double-layer stochastic(DS)nanowire network architecture neuromorphic computation nanowire network reservoir computing time series prediction

维普期刊数据库

Bayesian neural network enhancing reliability against conductance drift for memristor neural networks

在线全文

学校读者我要写书评

暂无评论

Science China(Information Sciences) 2021年第6期64卷 100-111页

作者： Yue ZHOU Xiaofang HU Lidan WANG shukai duan College of Electronics and Information Engineering Southwest University College of Artificial Intelligence Southwest University

The hardware implementation of neural networks based on memristor crossbar array provides a promising paradigm for neuromorphic computing. However, the existence of memristor conductance drift harms the reliability of the deployed neural network, which seriously hinders the practical application of memristor-based neuromorphic computing. In this paper, the impact of different types of conductance drift on the weight realized by memristors is investigated and analyzed. Then, utilizing the weight uncertainty introduced by conductance drift, we propose a weight optimization method based on the Bayesian neural network, which can greatly improve the network performance. Furthermore, an ensemble approach is proposed to enhance network reliability without increasing training cost or crossbar array resources. Finally, the effectiveness of the proposed scheme is verified through a series of experiments. In addition, the proposed scheme can be easily integrated into the implementation of neuromorphic computing, which can provide a better guarantee for its large-scale application.

关键词： conductance drift neuromorphic computing Bayesian neural network memristor crossbar array network reliability

Reconfigurable logic circuit design for stateful Boolean logic computing

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Science China(Information Sciences) 2021年第8期64卷 260-261页

作者： Li LUO Zhekang DONG Xiaofang HU Lidan WANG shukai duan College of Electronic and Information Engineering Southwest University Brain-inspired Computing & Intelligent Control of Chongqing Key Lab School of Electronics and Information Hangzhou Dianzi University College of Artificial Intelligence Southwest University

Dear editor,The conventional von Neumann computer system has the memory wall problem [1], which limits the computation speed and causes high energy and latency of the computing system. To realize computing systems able to process massive data and complex computing tasks with high efficiency,a key and viable approach is in-memory computing.Memristor-based stateful logic design is a promising candidate for realizing the in-memory logic computing [2].

关键词： Reconfigurable logic circuit design for stateful Boolean logic computing

Bayesian random Fourier filters for Gaussian noises

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Science China(Information Sciences) 2018年第12期61卷 214-216页

作者： Shiyuan WANG Wanli WANG shukai duan Lidan WANG Chi K.TSE College of Electronic and Information Engineering Southwest University Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing Department of Electronic and Information Engineering Hong Kong Polytechnic University

Dear editor,Signal processing algorithms are generally used to identify an unknown system, and can be classified as batch algorithms and online learning algorithms(OLAs). Batch algorithms are applied to offline scenar... 详细信息

关键词： Bayesian random Fourier filters for Gaussian noises

Analog memristive memory with applications in audio signal processing

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Science China(Information Sciences) 2014年第4期57卷 243-257页

作者： duan shukai HU XiaoFang WANG LiDan LI ChuanDong School of Electronics and Information Engineering Southwest University Department of Mechanical and Biomedical Engineering City University of Hong Kong

Since the development of the HP memristor,much attention has been paid to studies of memristive devices and applications,particularly memristor-based nonvolatile semiconductor memory.Owing to its unique properties,theoretically,one could restart a memristor-based computer immediately without the need for reloading the data.Further,current memories are mainly binary and can store only ones and zeros,whereas memristors have multilevel states,which means a single memristor unit can replace many binary transistors and realize higher-density memory.It is believed that memristors can also implement analog storage besides binary and multilevel information memory.In this paper,an implementation scheme for analog memristive memory is considered.A charge-controlled memristor model is derived and the corresponding SPICE model is constructed.Special write and read operations are demonstrated through numerical analysis and circuit simulations.In addition,an audio analog record/play system using a memristor crossbar array is designed.This system can provide great storage capacity(long recording time)and high audio quality with a simple small circuit structure.A series of computer simulations and analyses verify the effectiveness of the proposed scheme.

关键词： memristor analog memory circuit simulation record/play system audio signal storage

A spintronic memristive circuit on the optimized RBF-MLP neural network

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Chinese Physics B 2022年第11期31卷 272-283页

作者：葛源李杰蒋文武王丽丹段书凯 School of Artificial Intelligence Southwest UniversityChongqing 400715China Chongqing Brain Science Collaborative Innovation Center Chongqing 400715China Brain-inspired Computing and Intelligent Control of Chongqing Key Laboratory Chongqing 400715China National&Local Joint Engineering Laboratory of Intelligent Transmission and Control Technology Chongqing 400715China

A radial basis function network(RBF)has excellent generalization ability and approximation accuracy when its parameters are set appropriately.However,when relying only on traditional methods,it is difficult to obtain optimal network parameters and construct a stable model as well.In view of this,a novel radial basis neural network(RBF-MLP)is proposed in this article.By connecting two networks to work cooperatively,the RBF’s parameters can be adjusted adaptively by the structure of the multi-layer perceptron(MLP)to realize the effect of the backpropagation updating error.Furthermore,a genetic algorithm is used to optimize the network’s hidden layer to confirm the optimal neurons(basis function)number automatically.In addition,a memristive circuit model is proposed to realize the neural network’s operation based on the characteristics of spin memristors.It is verified that the network can adaptively construct a network model with outstanding robustness and can stably achieve 98.33%accuracy in the processing of the Modified National Institute of Standards and Technology(MNIST)dataset classification task.The experimental results show that the method has considerable application value.

关键词： radial basis function network(RBF) genetic algorithm spintronic memristor memristive circuit

维普期刊数据库

Memristive crossbar array with applications in image processing

在线全文

学校读者我要写书评

暂无评论

Science China(Information Sciences) 2012年第2期55卷 461-472页

作者： HU XiaoFang,duan shukai,WANG LiDan & LIAO XiaoFeng School of Electronics and Information Engineering,Southwest University,Chongqing 400715,China School of Electronics and Information Engineering Southwest University Chongqing China

A memristor is a kind of nonlinear resistor with memory capacity.Its resistance changes with the amount of charge or flux passing through it.As the fourth fundamental circuit element,it has huge potential applications in many fields,and has been expected to drive a revolution in circuit theory.Through numerical simulations and circuitry modeling,the basic theory and properties of memristors are analyzed,and a memristor-based crossbar array is then proposed.The array can realize storage and output for binary,grayscale and color images.A series of computer simulations demonstrates the effectiveness of the proposed scheme.Owing to the advantage of the memristive crossbar array in parallel information processing,the proposed method is expected to be used in high-speed image processing.

关键词： memristor crossbar array modeling and simulation image storage image output

Two-dimensional ballistic transistors for advanced-node integrated circuits

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

National Science Review 2024年第3期11卷 9-10页

作者： Jia Li Xidong duan Hunan Provincial Key Laboratory of Two-Dimensional Materials State Key Laboratory for Chemo/Biosensing and Chemometrics College of Chemistry and Chemical Engineering Hunan University

As the feature size of metal-oxide-semiconductor-field-effect-transistors(MOSFETs) in integrated circuits(ICs)is reduced to sub-10-nm, the traditional channel materials are plagued by enhanced scattering and short-cha... 详细信息

关键词： CONTACT

A FAS approach for stabilization of generalized chained forms: part 1. Discontinuous control laws

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Science China(Information Sciences) 2024年第2期67卷 118-143页

作者： Guang-Ren duan Center for Control Theory and Guidance Technology Harbin Institute of Technology Center for Control Science and Technology Southern University of Science and Technology

In this paper, a type of general nonholonomic systems is proposed, which contains both the Brockett’s two example systems, and their extended n-dimensional chained forms, as special cases. For the stabilization of such systems, a stabilizing controller is proposed based on the fully actuated system(FAS)approach, which is discontinuous at the origin but time-invariant when the open-loop system is time-invariant,and drives the feasible trajectories of the system to the origin exponentially. Furthermore, the proposed FAS approach is also extended to the sub-normal system case and the time-delay system case.

关键词： nonholonomic systems feedback stabilization exponential convergence sub-fully actuated systems time-delay systems