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Experimental demonstration of 220-GHz terahertz signals wireless transmission over 4.6 km

science China(information sciences) 2025年第1期68卷 386-388页

作者： Yi WEI Jianjun YU Mingxu WANG Xiongwei YANG Qiutong ZHANG Jingwen TAN Bing ZHANG Ying WU Yang HAN Peng TIAN Wen ZHOU Kaihui WANG Feng ZHAO State Key Laboratory of ASIC and System Key Laboratory for Information Science of Electromagnetic Waves (MoE)School of Information Science and Technology Fudan University School of Electronic Engineering Xi'an University of Posts and Telecommunications

The advancement of terahertz (THz) communication technology drives the evolution of wireless communication systems,offering novel pathways and technical means for the development of future 6G communication *** wireless communication systems are often constrained by bandwidth limitations of electronic devices in high frequency ***,THz communication technology leverages the characteristics of electromagnetic waves to transcend these limitations,enabling communication athigher frequencies and wider bandwidths.

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Fractal autoencoder with redundancy regularization for unsupervised feature selection

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science China(information sciences) 2025年第2期68卷 89-102页

作者： Meiting SUN Fangyu LI Honggui HAN School of Information Science and Technology Beijing University of Technology Beijing Key Laboratory of Computational Intelligence and Intelligent System Engineering Research Center of Digital Community Ministry of Education Beijing Institute of Artificial Intelligence

Feature selection is a crucial step in data preprocessing because feature selection reduces the dimensionality of data by eliminating irrelevant and redundant features. Since manual labeling is expensive, unsupervised feature selection has received increasing attention in recent years. However, existing unsupervised feature selection methods tend to prioritize selecting highly correlated features over exploring feature diversity. Thus, a regularized fractal autoencoder(RFAE) method is proposed to select informative features in an unsupervised way. Specifically, the fractal autoencoder network extends autoencoders to construct a correspondence neural network and a selection neural network. The correspondence neural network exploits interfeature correlations and the selection neural network selects the informative features. A redundancy regularization strategy consists of a redundancy elimination regularization term based on the dependency between features and a sparse regularization term based on the group lasso. The redundancy regularization strategy eliminates feature subset redundancy and enhances network generalization ability. Extensive experimental results on six publicly available datasets show that the proposed RFAE outperforms the compared methods regarding clustering accuracy and classification accuracy. Moreover, the proposed RFAE achieves acceptable computation efficiency.

关键词： unsupervised feature selection fractal autoencoder correspondence neural network selection neural network redundancy regularization strategy

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Online Fault-Tolerant Tracking Control With Adaptive Critic for Nonaffine Nonlinear systems

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 215-227页

作者： Ding Wang Lingzhi Hu Xiaoli Li Junfei Qiao IEEE the School of Information Science and Technology Beijing Key Laboratory of Computational Intelligence and Intelligent SystemBeijing Laboratory of Smart Environmental Protection and Beijing Institute of Artificial Intelligence Beijing University of Technology

In this paper, a fault-tolerant-based online critic learning algorithm is developed to solve the optimal tracking control issue for nonaffine nonlinear systems with actuator ***, a novel augmented plant is constructed by fusing the system state and the reference trajectory, which aims to transform the optimal fault-tolerant tracking control design with actuator faults into the optimal regulation problem of the conventional nonlinear error system. Subsequently, in order to ensure the normal execution of the online learning algorithm, a stability criterion condition is created to obtain an initial admissible tracking policy. Then, the constructed model neural network(NN) is pretrained to recognize the system dynamics and calculate trajectory control. The critic and action NNs are constructed to output the approximate cost function and approximate tracking control,respectively. The Hamilton-Jacobi-Bellman equation of the error system is solved online through the action-critic framework. In theoretical analysis, it is proved that all concerned signals are uniformly ultimately bounded according to the Lyapunov *** tracking control law can approach the optimal tracking control within a finite approximation error. Finally, two experimental examples are conducted to indicate the effectiveness and superiority of the developed fault-tolerant tracking control scheme.

关键词： Adaptive critic control neural network (NN) nonaffine nonlinear systems online fault-tolerant tracking design uniform ultimate boundedness

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A MIMO Neural Network Integrated with Maximum Likelihood Phase Recovery for Transoceanic Coherent Transmission

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Journal of Lightwave technology 2025年第12期43卷 5536-5544页

作者： Wang, Kaihui Wang, Chen Zheng, Tianqi Long, Jianyu Sang, Bohan Zhou, Wen Yu, Jianjun Fudan University State Key Laboratory of ASIC and System School of Information Science and Technology Shanghai200433 China

We proposed a low-complexity multi-input multi-output neural network integrated with a maximum likelihood phase recovery algorithm (MIMO-NN-BMLPR), which is adopted in long-haul coherent optical communication. Neural network based equalization can effectively overcome the nonlinear distortions induced during long-haul transmission. However, the forward neural network equalizer is difficult to track the phase of coherent optical signals. We integrate an additional maximum likelihood phase recovery layer with the MIMO-NN structure so that the phase noise can be compensated. In this work, 8-channel 100-GBaud dual-polarization (DP) PS-16QAM signals are successfully transmitted over 6400km and satisfy the normalized generalized mutual information (NGMI) threshold at 0.86. The proposed MIMO-NN-BMLPR integrates the low-complexity phase estimation with the NNE to improve the performance. Compared with the traditional DSP structure, the proposal prolongs the distance by 48.84% with a 39.80% complexity reduction. © 1983-2012 IEEE.

关键词： Optical communication

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Enhanced Tube-Based Event-Triggered Stochastic Model Predictive Control With Additive Uncertainties

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IEEE/CAA Journal of Automatica Sinica 2025年第3期12卷 596-605页

作者： Chenxi Gu Xinli Wang Kang Li Xiaohong Yin Shaoyuan Li Lei Wang the School of Control Science and Engineering Shandong University IEEE the School of Electronic and Electrical Engineering University of Leeds the Qingdao University of Science and Technology the Department of Automation Shanghai Jiao Tong University the Key Laboratory of System Control and Information Processing Ministry of Education of China

This paper proposes an event-triggered stochastic model predictive control for discrete-time linear time-invariant(LTI) systems under additive stochastic disturbances. It first constructs a probabilistic invariant set and a probabilistic reachable set based on the priori knowledge of system *** with enhanced robust tubes, the chance constraints are then formulated into a deterministic form. To alleviate the online computational burden, a novel event-triggered stochastic model predictive control is developed, where the triggering condition is designed based on the past and future optimal trajectory tracking errors in order to achieve a good trade-off between system resource utilization and control performance. Two triggering parameters σ and γ are used to adjust the frequency of solving the optimization problem. The probabilistic feasibility and stability of the system under the event-triggered mechanism are also examined. Finally, numerical studies on the control of a heating, ventilation, and air conditioning(HVAC) system confirm the efficacy of the proposed control.

关键词： Event-triggered mechanism heating, ventilation, and air conditioning (HVAC) control probabilistic reachable set stochastic model predictive control

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A Zeroth-Order Adaptive Frank–Wolfe Algorithm for Resource Allocation in Internet of Things: Convergence Analysis

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IEEE Internet of Things Journal 2025年第11期12卷 17765-17779页

作者： Liu, Muhua Zhu, Yajie Wu, Qingtao Ji, Zhihang Zhao, Xuhui Zheng, Ruijuan Henan University of Science and Technology Longmen Laboratory School of Information Engineering Luoyang471023 China Henan University of Science and Technology School of Information Engineering Luoyang471023 China

A pivotal problem in the Internet of Things (IoT) is resource allocation, where the goal is to optimize allocation strategies of IoT resources. In general, resource allocation problems are formulated as constrained optimization problems, which can be effectively solved by the zeroth-order Frank-Wolfe algorithm. However, the existing zeroth-order Frank-Wolfe algorithms suffer from slow convergence since they scale the zeroth-order gradient in all directions. For this reason, we propose a faster zeroth-order Frank-Wolfe algorithm, referred to as ZO-AdaSFW, which incorporates adaptive gradient methods and the variance-reduced technique (SPIDER) into the zeroth-order Frank-Wolfe algorithm. Moreover, ZO-AdaSFW can achieve the convergence rate of O(T-1) in the convex setting, where T is the time horizon. Meanwhile, we also prove that ZO-AdaSFW has the best-known convergence rate O(T-1/2) among zeroth-order algorithms in the nonconvex setting. In addition, the experimental results show that the performance of ZO-AdaSFW outperforms state-of-the-art zeroth-order Frank-Wolfe algorithms on different applications. © 2014 IEEE.

关键词： Optimization algorithms

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Attack and Defense Game with Intuitionistic Fuzzy Payoffs in Infrastructure Networks

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Tsinghua science and technology 2025年第1期30卷 384-401页

作者： Yibo Dong Jin Liu Jiaqi Ren Zhe Li Weili Li Science and Technology on Information Systems Engineering Laboratory National University of Defense TechnologyChangsha 410073China

Due to our increasing dependence on infrastructure networks,the attack and defense game in these networks has draw great concerns from security ***,when it comes to evaluating the payoffs in practical attack and defense games in infrastructure networks,the lack of consideration for the fuzziness and uncertainty of subjective human judgment brings forth significant challenges to the analysis of strategic interactions among decision *** paper employs intuitionistic fuzzy sets(IFSs)to depict such uncertain payoffs,and introduce a theoretical framework for analyzing the attack and defense game in infrastructure networks based on intuitionistic fuzzy *** take the changes in three complex network metrics as the universe of discourse,and intuitionistic fuzzy sets are employed based on this universe of discourse to reflect the satisfaction of decision *** employ an algorithm based on intuitionistic fuzzy theory to find the Nash equilibrium,and conduct experiments on both local and global *** show that:(1)the utilization of intuitionistic fuzzy sets to depict the payoffs of attack and defense games in infrastructure networks can reflect the unique characteristics of decision makers’subjective preferences.(2)the use of differently weighted proportions of the three complex network metrics has little impact on decision makers’choices of different strategies.

关键词： infrastructure networks attack and defense game intuitionistic fuzzy set Nash equilibrium

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Identification algorithm of low-count energy spectra under short-duration measurement based on heterogeneous sample transfer

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Nuclear science and Techniques 2025年第3期36卷 12-26页

作者： Hao-Lin Liu Hai-Bo Ji Jiang-Mei Zhang Jing Lu School of Information Engineering Southwest University of Science and TechnologyMianyang 621010China Department of Automation University of Science and Technology of ChinaHefei 230026China Fundamental Science on Nuclear Wastes and Environment Safety Laboratory Southwest University of Science and TechnologyMianyang 621010China School of Automation and Information Engineering Sichuan University of Science and EngineeringZigong 643000China

In scenarios such as vehicle radiation monitoring and unmanned aerial vehicle radiation detection,rapid measurements using a NaI(Tl)detector often result in low photon counts,weak characteristic peaks,and significant statistical *** issues can lead to potential failures in peak-searching-based identification *** address the low precision associated with short-duration measurements of radionuclides,this paper proposes an identification algorithm that leverages heterogeneous spectral transfer to develop a low-count energy spectral identification *** experiments demonstrated that transferring samples from 26 classes of simulated heterogeneous gamma spectra aids in creating a reliable model for measured gamma *** only 10%of target domain samples used for training,the accuracy on real low-count spectral samples was 95.56%.This performance shows a significant improvement over widely employed full-spectrum analysis methods trained on target domain *** proposed method also exhibits strong generalization capabilities,effectively mitigating overfitting issues in low-count energy spectral classification under short-duration measurements.

关键词： Radionuclide identification Low-count Gamma energy spectral analysis Heterogeneous Transfer learning

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Observation of memristive behavior in PDMS-glass nanofluidic chip

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Nano Research 2025年第2期18卷 725-732页

作者： Weiling Sun Yike Xiao Pingyuan Yan Fei Sun Xuan Zhang Chuanxiang Sheng Qi Wang Yefeng Yu School of Microelectronics Nanjing University of Science and TechnologyNanjing 210094China Key Laboratory of New Membrane Materials Ministry of Industry and Information TechnologySchool of Environmental and Biological EngineeringNanjing University of Science and TechnologyNanjing 210094China Department of Optical Science and Engineering School of Information Science and TechnologyFudan UniversityShanghai 200433China

Nanofluidic memristors,which use ions in electrolyte solutions as carriers,have been developed rapidly and brought new opportunities for the development of neuromorphic *** the transport and accumulation of ions in nanochannels to process information is an endeavor to realize the nanofluidic *** this study,we report a new nanofluidic memristor,which is a polydimethylsiloxane(PDMS)-glass chip with two platinum(Pt)electrodes and well-aligned multi-nanochannels within PDMS for ion enrichment and *** device not only exhibits typical bipolar memristive behavior and ion current rectification(ICR)but also demonstrates excellent endurance,maintaining stable performance after 100 sweep *** systematically investigate the key factors affecting ion transport behavior in this *** results show that the ICR ratio of the current-voltage(I-V)hysteresis curves decreases with increasing scan rate and solution *** potential measurements are introduced to reveal that the PDMS surface carries more negative charges in higher pH solutions,resulting in more pronounced memristive and ICR ***,our memristor can simulate short-term synaptic plasticity,such as paired-pulse facilitation(PPF)and paired-pulse depression(PPD),with a relatively low energy consumption of 12 pJ per spike per ***,the inherent accessibility and robustness of our nanofluidic memristors facilitate the optimization of device structure and *** important observations and investigations lay a foundation for advancing energy-saving and efficient neuromorphic computing.

关键词： polydimethylsiloxane(PDMS)-glass chip nanofluidic memristor nanochannel short-term synaptic plasticity(STP)

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Turbulent drag reduction by sector-shaped counter-flow dielectric barrier discharge plasma actuator

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Chinese Physics B 2025年第2期34卷 362-370页

作者： Borui Zheng Shaojie Qi Minghao Yu Jianbo Zhang Linwu Wang Dongliang Bian School of Automation and Information Engineering Xi’an University of TechnologyXi’an 710048China School of Mechanical and Precision Instrument Engineering Xi’an University of TechnologyXi’an 710048China Science and Technology on Plasma Dynamics Laboratory Air Force Engineering UniversityXi’an 710038China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an 710048China Shaanxi University Key Laboratory of Photonic Power Devices and Discharge Regulation Xi’an 710048China

The primary objective in aircraft transportation is to minimize turbulent drag, thereby conserving energy and reducing emissions. We propose a sector-shaped counter-flow dielectric barrier discharge plasma actuator, which leverages jet synthesis for drag reduction. A drag control experiment was conducted in a low-speed wind tunnel with a controlled flow velocity of 9.6 m/s(Re = 1.445 × 10^(4)). This study investigated the effects of varying pulse frequencies and actuation voltages on the turbulent boundary layer. Using a hot-wire measurement system, we analyzed the pulsating and time-averaged velocity distributions within the boundary layer to evaluate the streamwise turbulent drag reduction. The results show that the local TDR decreases as the pulse frequency increases, reaching a maximum reduction of approximately 20.97% at a pulse frequency of 50 Hz. In addition, as the actuation voltage increases, the friction coefficient decreases, increasing the drag reduction rate. The maximum drag reduction of approximately 33.34% is achieved at an actuation voltage of 10 kV.

关键词： plasma flow control turbulent boundary layer turbulent drag reduction

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