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The Combined Effect of Spin-Transfer Torque and Voltage-Controlled Strain Gradient on Magnetic Domain-Wall Dynamics:Toward Tunable Spintronic Neuron

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Chinese Physics Letters 2024年第5期41卷 120-137页

作者：郁国良何鑫岩施胜宾邱阳朱明敏王嘉维李燕李元勋王杰周浩淼 College of information engineering China Jiliang UniversityHangzhou 310018China The Key Laboratory of Electromagnetic Wave information Technology and Metrology of zhejiang Province Hangzhou 310018China department of engineering Mechanics Zhejiang UniversityHangzhou 310027China School of electronic Science and engineering University of Electronic Science and Technology of ChinaChengdu 611731China

Magnetic domain wall(DW), as one of the promising information carriers in spintronic devices, have been widely investigated owing to its nonlinear dynamics and tunable properties. Here, we theoretically and numerically demonstrate the DW dynamics driven by the synergistic interaction between current-induced spin-transfer torque(STT) and voltage-controlled strain gradient(VCSG) in multiferroic heterostructures. Through electromechanical and micromagnetic simulations, we show that a desirable strain gradient can be created and it further modulates the equilibrium position and velocity of the current-driven DW motion. Meanwhile, an analytical Thiele's model is developed to describe the steady motion of DW and the analytical results are quite consistent with the simulation data. Finally, we find that this combination effect can be leveraged to design DW-based biological neurons where the synergistic interaction between STT and VCSG-driven DW motion as integrating and leaking motivates mimicking leaky-integrate-and-fire(LIF) and self-reset function. Importantly, the firing response of the LIF neuron can be efficiently modulated, facilitating the exploration of tunable activation function generators, which can further help improve the computational capability of the neuromorphic system.

关键词： tunable synergistic integrating

information-Theoretic Limits on Compression of Semantic information

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China Communications 2024年第7期21卷 1-16页

作者： Tang Jiancheng Yang Qianqian Zhang Zhaoyang College of information Science and electronic engineering Zhejiang UniversityHangzhou 310007China

As conventional communication systems based on classic information theory have closely approached Shannon capacity,semantic communication is emerging as a key enabling technology for the further improvement of communication ***,it is still unsettled on how to represent semantic information and characterise the theoretical limits of semantic-oriented compression and *** this paper,we consider a semantic source which is characterised by a set of correlated random variables whose joint probabilistic distribution can be described by a Bayesian *** give the information-theoretic limit on the lossless compression of the semantic source and introduce a low complexity encoding method by exploiting the conditional *** further characterise the limits on lossy compression of the semantic source and the upper and lower bounds of the rate-distortion *** also investigate the lossy compression of the semantic source with two-sided information at the encoder and decoder,and obtain the corresponding rate distortion *** prove that the optimal code of the semantic source is the combination of the optimal codes of each conditional independent set given the side information.

关键词： rate distortion semantic communication semantic compression

Non-Deterministic Liveness-Enforcing Supervisor Tolerant to Sensor-Reading Modification Attacks

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 240-248页

作者： Dan You Shouguang Wang IEEE the School of information and electronic engineering Sussex Artificial Intelligence InstituteZhejiang Gongshang UniversityHangzhou 310018China

In this paper, we study the supervisory control problem of discrete event systems assuming that cyber-attacks might occur. In particular, we focus on the problem of liveness enforcement and consider a sensor-reading modification attack(SM-attack) that may disguise the occurrence of an event as that of another event by intruding sensor communication channels. To solve the problem, we introduce non-deterministic supervisors in the paper, which associate to every observed sequence a set of possible control actions offline and choose a control action from the set randomly online to control the system. Specifically, given a bounded Petri net(PN) as the reference formalism and an SMattack, an algorithm that synthesizes a liveness-enforcing nondeterministic supervisor tolerant to the SM-attack is proposed for the first time.

关键词： Cyber-attacks cyber-physical system(CPS) liveness non-deterministic supervisors Petri net(PN)

Visible Light Indoor Positioning System Based on Pisarenko Harmonic Decomposition and Neural Network

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Chinese Journal of electronics 2024年第1期33卷 195-203页

作者： Li ZHAO Yi REN Qi WANG Lange DENG Feng ZHANG School of electronic information engineering Xi’an Technological University

Visible-light indoor positioning is a new generation of positioning technology that can be integrated into smart lighting and optical communications. The current received signal strength(RSS)-based visible-light positioning systems struggle to overcome the interferences of background and indoor-reflected noise. Meanwhile, when ensuring the lighting, it is impossible to use the superposition of each light source to accurately distinguish light source information; furthermore, it is difficult to achieve accurate positioning in complex indoor environments. This study proposes an indoor positioning method based on a combination of power spectral density detection and a neural network. The system integrates the mechanism for visible-light radiation detection with RSS theory, to build a back propagation neural network model fitting for multiple reflection channels. Different frequency signals are loaded to different light sources at the beacon end, and the characteristic frequency and power vectors are obtained at the location end using the Pisarenko harmonic decomposition method. Then, a complete fingerprint database is established to train the neural network model and conduct location tests. Finally, the location effectiveness of the proposed algorithm is verified via actual positioning experiments. The simulation results show that, when four groups of sinusoidal waves with different frequencies are superimposed with white noise, the maximum frequency error is 0.104 Hz and the maximum power error is 0.0362 W. For the measured positioning stage, a 0.8 m × 0.8 m × 0.8 m solid wood stereoscopic positioning model is constructed, and the average error is 4.28 cm. This study provides an effective method for separating multi-source signal energies, overcoming background noise, and improving indoor visible-light positioning accuracies.

关键词： Neural networks Measurement uncertainty Position measurement Harmonic analysis Light emitting diodes Frequency estimation Indoor positioning systems

Gradient sparsification for efficient wireless federated learning with differential privacy

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Science China(information Sciences) 2024年第4期67卷 272-288页

作者： Kang WEI Jun LI Chuan MA Ming DING Feng SHU Haitao ZHAO Wen CHEN Hongbo ZHU School of electronic and Optical engineering Nanjing University of Science and Technology zhejiang Lab Key Laboratory of Computer Network and information Integration(Southeast university) Ministry of Education Data61 Commonwealth Scientific and Industrial Research Organisation School of information and Communication engineering Hainan University School of Communications and information engineering Nanjing University of Posts and Telecommunications School of electronic information and Electrical engineering Shanghai Jiao Tong University

Federated learning(FL) enables distributed clients to collaboratively train a machine learning model without sharing raw data with each other. However, it suffers from the leakage of private information from uploading models. In addition, as the model size grows, the training latency increases due to the limited transmission bandwidth and model performance degradation while using differential privacy(DP)protection. In this paper, we propose a gradient sparsification empowered FL framework with DP over wireless channels, to improve training efficiency without sacrificing convergence performance. Specifically, we first design a random sparsification algorithm to retain a fraction of the gradient elements in each client’s local model, thereby mitigating the performance degradation induced by DP and reducing the number of transmission parameters over wireless channels. Then, we analyze the convergence bound of the proposed algorithm, by modeling a non-convex FL problem. Next, we formulate a time-sequential stochastic optimization problem for minimizing the developed convergence bound, under the constraints of transmit power, the average transmitting delay, as well as the client’s DP requirement. Utilizing the Lyapunov drift-plus-penalty framework, we develop an analytical solution to the optimization problem. Extensive experiments have been implemented on three real-life datasets to demonstrate the effectiveness of our proposed algorithm. We show that our proposed algorithms can fully exploit the interworking between communication and computation to outperform the baselines, i.e., random scheduling, round robin, and delay-minimization algorithms.

关键词： federated learning differential privacy gradient sparsification Lyapunov drift convergence analysis

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A 3D-printed microhemispherical shell resonator with electrostatic tuning for a Coriolis vibratory gyroscope

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Microsystems & Nanoengineering 2024年第2期10卷 25-35页

作者： Baoyin Hou Ye Zhu Chaofan He Weidong Wang Zhi Ding Wen He Yong He Lufeng Che College of information Science and electronic engineering Zhejiang UniversityHangzhou310027China Center for Microelectronics Shaoxing InstituteZhejiang UniversityShaoxing312035China State Key Laboratory of Fluid Power and Mechatronic Systems Zhejiang UniversityHangzhou310058China School of Mechanical engineering Zhejiang UniversityHangzhou310058China

The emergence of microhemispherical resonant gyroscopes,which integrate the advantages of exceptional stability and long lifetime with miniaturization,has afforded new possibilities for the development of whole-angle ***,existing methods used for manufacturing microhemispherical resonant gyroscopes based on MEMS technology face the primary drawback of intricate and costly ***,we report the design,fabrication,and characterization of the first 3D-printable microhemispherical shell resonator for a Coriolis vibrating *** remarkably achieve fabrication in just two steps bypassing the dozen or so steps required in traditional *** utilizing the intricate shaping capability and ultrahigh precision offered by projection microstereolithography,we fabricate 3D high-aspect-ratio resonant structures and controllable capacitive air gaps,both of which are extremely difficult to obtain via MEMS *** addition,the resonance frequency of the fabricated resonators can be tuned by electrostatic forces,and the fabricated resonators exhibit a higher quality factor in air than do typical MEMS microhemispherical *** work demonstrates the feasibility of rapidly batch-manufacturing microhemispherical shell resonators,paving the way for the development of microhemispherical resonator gyroscopes for portable inertial ***,this particular design concept could be further applied to increase uptake of resonator tools in the MEMS community.

关键词： resonator tuning electrostatic

Asymmetric time-varying integral barrier Lyapunov function based adaptive optimal control for nonlinear systems with dynamic state constraints

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Frontiers of information Technology & electronic engineering 2024年第6期25卷 887-902页

作者： Yan WEI Mingshuang HAO Xinyi YU Linlin OU College of information engineering Zhejiang University of TechnologyHangzhou 310023China

This paper investigates the issue of adaptive optimal tracking control for nonlinear systems with dynamic state *** asymmetric time-varying integral barrier Lyapunov function(ATIBLF)based integral reinforcement learning(IRL)control algorithm with an actor–critic structure is first *** ATIBLF items are appropriately arranged in every step of the optimized backstepping control design to ensure that the dynamic full-state constraints are never ***,optimal virtual/actual control in every backstepping subsystem is decomposed with ATIBLF items and also with an adaptive optimized ***,neural networks are used to approximate the gradient value *** to the Lyapunov stability theorem,the boundedness of all signals of the closed-loop system is proved,and the proposed control scheme ensures that the system states are within predefined compact ***,the effectiveness of the proposed control approach is validated by simulations.

关键词： State constraints Asymmetric time-varying integral barrier Lyapunov function(ATIBLF) Adaptive optimal control Nonlinear systems

An Incentive Mechanism for Federated Learning:A Continuous Zero-Determinant Strategy Approach

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 88-102页

作者： Changbing Tang Baosen Yang Xiaodong Xie Guanrong Chen Mohammed A.A.Al-qaness Yang Liu IEEE the College of Physics and electronic information engineering Zhejiang Normal UniversityUniversityJinhua 321004China the School of Mathematical Sciences Zhejiang Normal UniversityJinhua 321004China the department of Electrical engineering City University of Hong KongHong KongChina Key Laboratory of Intelligent Education Technology and Application of zhejiang Province Jinhua 321004China

As a representative emerging machine learning technique, federated learning(FL) has gained considerable popularity for its special feature of “making data available but not visible”. However, potential problems remain, including privacy breaches, imbalances in payment, and inequitable *** shortcomings let devices reluctantly contribute relevant data to, or even refuse to participate in FL. Therefore, in the application of FL, an important but also challenging issue is to motivate as many participants as possible to provide high-quality data to FL. In this paper, we propose an incentive mechanism for FL based on the continuous zero-determinant(CZD) strategies from the perspective of game theory. We first model the interaction between the server and the devices during the FL process as a continuous iterative game. We then apply the CZD strategies for two players and then multiple players to optimize the social welfare of FL, for which we prove that the server can keep social welfare at a high and stable level. Subsequently, we design an incentive mechanism based on the CZD strategies to attract devices to contribute all of their high-accuracy data to ***, we perform simulations to demonstrate that our proposed CZD-based incentive mechanism can indeed generate high and stable social welfare in FL.

关键词： Federated learning(FL) game theory incentive mechanism machine learning zero-determinant strategy

Near-field wideband beam training for ELAA with uniform circular array

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Science China(information Sciences) 2024年第6期67卷 370-383页

作者： Yuhao CHEN Linglong DAI department of electronic engineering Tsinghua UniversityBeijing National Research Center for Information Science and Technology (BNRist)

Extremely large-scale antenna array(ELAA) at millimeter wave(mmWave) and Terahertz(THz)band has been considered a key technology for combating high attenuation in high-frequency bands in future6G communications. Uniform circular arrays(UCAs) have attracted much attention because of their ability to provide flat beamforming gain at all angles. To realize efficient beamforming, beam training is widely used to acquire channel state information. However, with a large antenna number, the beam training overhead in ELAA systems becomes overwhelming. Moreover, with a large bandwidth, the beam defocus effect severely degrades beam training accuracy. To address these issues, this paper proposes a frequency-dependent focusing(FDF)-based beam training scheme to realize effective beam training in near-field wideband ELAA systems with UCA. Specifically, we first analyze the FDF property of UCA, where signals at different subcarriers can simultaneously focus on different distances. Then, by exploiting the FDF property to search different distances using different subcarriers simultaneously, we design a hierarchical codebook and propose an FDFbased beam training scheme. To reveal the effectiveness of the proposed scheme, we compare its necessary beam training overhead with that of existing schemes. Finally, the simulation results demonstrate that the proposed scheme can achieve accurate beam training in near-field wideband UCA systems with a low beam training overhead.

关键词： extremely large-scale antenna array (ELAA) uniform circular array (UCA) near-field wideband beam training

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