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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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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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Hierarchical Learning-Based Integrated Robust Optimal Control for Nonlinear systems

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IEEE Transactions on systems, Man, and Cybernetics: systems 2025年第5期55卷 3119-3129页

作者： Zhang, Jiacheng Wang, Jingjing Han, Honggui Hou, Ying Huang, Yanting Beijing University of Technology Faculty of Information Technology Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing100124 China

The optimal control of nonlinear systems is crucial to improve system performance. However, the uncertainties of cost functions and systems dynamics make it difficult to solve the optimal control laws. To cope with this problem, a hierarchical learning-based integrated robust optimal control (HL-IROC) method is proposed in this article. The merits of the proposed HL-IROC method are three aspects: First, a hierarchical learning-based integrated optimal control (HL-IOC) scheme, contains a system dynamic learning layer and a cost function learning layer, is designed to transform the original optimal control problem into an integrated optimization problem with control laws as decision variables. Then, the relationships between cost functions and control laws are captured to overcome the difficulties brought by uncertainties in the optimal control process. Second, a global-local cooperative robust evolutionary optimization (GL-CREO) algorithm is proposed to obtain the optimal control laws. Then, a global-local robust searching strategy is employed to deal with two types of uncertainties for improving the robustness of control laws. Third, the convergence analysis of HL-IOC and GL-CREO is discussed in theory. In the experiments, the effectiveness of HL-IROC is illustrated with a nonlinear system and a wastewater treatment process. © 2013 IEEE.

关键词： Optimal control systems

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Metal-Frame Slot Antenna with a Small Ground Clearance for the Wi-Fi 6E Operation in Laptop Applications

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IEEE Transactions on Antennas and Propagation 2025年第5期73卷 3394-3399页

作者： Wu, Jiahao Yang, Guo-Min Wang, Yan Yan, Na Jin, Ya-Qiu Fudan University Key Laboratory for Information Science of Electromagnetic Waves School of Information Science and Technology Shanghai200433 China Fudan University State Key Laboratory of ASIC and System School of Microelectronics Shanghai200433 China

In this communication, a metal-frame slot antenna with a very small ground clearance for laptop is proposed. Regarding the antenna structure, it is an asymmetrical modified inverted T-shaped slot (AMITS) structure, which includes a long step slot arm, a short slot arm and a loop slit. The AMITS antenna is integrated with the metal casing connected with an inverted L-shaped strip, covering the 2.4/5/6 GHz frequency bands with four resonant modes excited. The antenna is analyzed and a prototype is fabricated and measured. The proposed AMITS antenna features a very-small ground clearance measuring merely 1.2 mm, covering a-10 dB impedance bandwidth of 160 MHz (2.33-2.49 GHz) and 2.4 GHz (4.92-7.32 GHz) with a peak efficiency of 70%. The low-profile, simple-structure AMITS antenna shows prospect for the narrow-bezel laptop in Wi-Fi 6E applications. © 1963-2012 IEEE.

关键词： Wi-Fi

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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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Infrared image super-resolution reconstruction based on residual fast fourier transform

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Multimedia Tools and Applications 2025年第9期84卷 6805-6823页

作者： Li, Xianguo Liu, Rui Yang, Yanli School of Electronics and Information Engineering Tiangong University Tianjin China Tianjin Key Laboratory of Optoelectronic Detection Technology and System Tianjin China

Infrared images have been widely used in military, civilian, and industrial fields. Due to the inherent limitations of sensors, infrared images usually have some disadvantages such as low resolution and blurred texture details. How to improve the resolution of infrared images without changing hardware devices has become a current research hotspot. Aiming at the problem that the existing infrared image super-resolution reconstruction methods do not utilize the image details sufficiently, this paper proposes an infrared image super-resolution reconstruction algorithm based on residual fast fourier transform(ISRRFT). The image features are extracted in both spatial domain and frequency domain, so as to fully extract the high-frequency and low-frequency information components of infrared images and improve the quality of reconstructed infrared images In addition, the learnable fast fourier transform loss function has been introduced, which is used in conjunction with the L1 loss function to calculate the loss from both the spatial and frequency domains, thus better optimizing the model parameters. The test results on three test sets, SR1280, IRData and Infrared20, show that the proposed algorithm has an optimal performance in terms of both objective and subjective evaluation metrics compared to current representative algorithms. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Image reconstruction

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Security Testing for Deep Learning Models in Multiple Scenarios 3rd

Security Testing for Deep Learning Models in Multiple Scenar...

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3rd International Conference on Machine Learning, Cloud Computing and Intelligent Mining, MLCCIM 2024

作者： Wu, Zhendong Li, Hu Zhang, Ming Lu, Shuaibing National Key Laboratory of Science and Technology on Information System Security Beijing China

ISBN: (纸本)9789819624676

Deep learning models are widely used in security-sensitive tasks such as facial recognition and autonomous driving. Security issues in deep models could have serious implications for people’s lives, such as life-threatening situations resulting from autonomous driving failures. To enhance the security of deep models, security testing is necessary before their formal deployment. Since different scenarios may involve different deep models, a security testing method that targets multiple scenarios would be more universally applicable. In this paper, we propose a security testing method for deep models that can be applied across multiple scenarios, primarily utilizing adversarial attacks to test the models. For the deep model under test, we first construct threat scenarios and then associate the model with datasets and adversarial attack methods. Subsequently, we generate adversarial examples to input into the deep model to check its accuracy in classification. Finally, we evaluate the success rate of adversarial attacks on the deep model. A high attack success rate indicates low model security, necessitating developers to employ adversarial training or other methods to enhance model security. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Adversarial machine learning

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FPGA Real-Time Deployment of Low-Complexity Volterra Equalizer Based on Pruning and Non-Uniform Quantization

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Journal of Lightwave technology 2025年第9期43卷 4183-4192页

作者： Sun, Xinda Wang, Kaihui Zhu, Zonghui Zhang, Long Gou, Yumeng Meng, Yuanxiao Chen, Yun Yu, Jianjun Fudan University Department of Communication Science and Engineering State Key Laboratory of ASIC and System Key Laboratory for Information Science of Electromagnetic Waves School of Information Science and Technology Shanghai 200433 China Fudan University Shanghai200433 China

Electronic nonlinear equalization technology is a promising signal impairments compensation technique with great development potential and wide application scenarios. However, its high complexity makes it challenging to implement in field-programmable gate array (FPGA). We propose a low-complexity real-time nonlinear equalization scheme based on FPGA, which can provide similar performance as traditional schemes but only occupies very low digital signal processing (DSP) resources. With the help of this scheme, by using pruning and non-uniform quantization, the computational complexity of a Volterra equalizer with 15 linear taps and 25 nonlinear taps is comparable to that of a Volterra equalizer with 8 linear taps and 4 nonlinear taps. By non-uniformly quantizing the taps of the equalizer, the quantization accuracy can be saved compared to uniform quantization, and after the taps are quantized, complex multiplication can be replaced by simple shift operations, simplifying the complexity of multiplication operations. The scheme of weight pruning and non-uniform quantization significantly reduces the required hardware resources and power consumption. We verify the proposed scheme in a decision-directed Volterra (DD-Volterra) equalizer, The equalizer was successfully deployed in a 230.4 MHz xcvu9pflgb2104-2-I Xilinx FPGA and achieved real-time IM/DD transmission of 29.4912 Gbit/s PAM4 signals over 25 km standard single-mode fiber (SSMF), meeting the 3.8 × 10-3 hard-decision forward error correction (HD-FEC) standard. The results show that the proposed low-complexity Volterra equalizer scheme can reduce DSP resources by up to 75.3% and power consumption by 26.2%. © 1983-2012 IEEE.

关键词： Forward error correction

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Impacts of Land–Atmosphere Coupling on Summer Extreme Hot-Humid Compound Events over Southern Eurasia under Different Sea Surface Temperature Backgrounds

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Advances in Atmospheric Sciences 2025年第4期42卷 744-760页

作者： Yajing QI Haishan CHEN Siguang ZHU State Key Laboratory of Climate System Prediction and Risk Management/Key Laboratory of Meteorological Disaster Ministry of Education/Collaborative Innovation Center on Forecast and Evaluation of Meteorological DisastersNanjing University of Information Science and TechnologyNanjing 210044China School of Atmospheric Sciences Nanjing University of Information Science and TechnologyNanjing 210044China

Land–atmosphere coupling and sea surface temperature(SST)anomalies both have essential impacts on weather and climate *** on the ERA5 reanalysis dataset and the CESM1.2.2 model,this study investigates the influence of land–atmosphere coupling on summer extreme hot-humid events(EHHE)over southern Eurasia under different SST *** results suggest that coupling causes near-surface air temperature increases that exceed 0.5℃.From 1961 to 2020,the frequency of EHHE has continuously increased,and is closely related to soil moisture anomalies in the northern Indian Peninsula(IDP)and the middle and lower reaches of the Yangtze River(YRB).Numerical simulations further demonstrate that land–atmosphere coupling raises the risk of EHHE by 25.4%.In a typical El Niño SST background state,intensified land–atmosphere coupling tends to produce notable increases in the frequency of *** dominant processes that land–atmosphere coupling affects the EHHE variations are evidently different between these two *** surface thermal anomalies predominate in the IDP,while moisture conditions are more critical in the *** warm SST anomalies exist,dry soil anomalies in the IDP are prominent,and evaporation is constrained,increasing sensible heat *** geopotential height anomalies are significant,combined with adiabatic warming induced by descending motion and a noticeable warm center in the near-surface *** southward shift of the westerly jet enhances divergence over *** anticyclonic circulation anomalies over the western Pacific are conducive to guiding moisture transport to the YRB,providing a favorable circulation background for the development of summer EHHE.

关键词： land-atmosphere coupling sea surface temperature extreme hot-humid events southern Eurasia

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Three-dimension collision-free trajectory planning of UAVs based on ADS-B information in low-altitude urban airspace

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Chinese Journal of Aeronautics 2025年第2期38卷 274-285页

作者： Chao DONG Yifan ZHANG Ziye JIA Yiyang LIAO Lei ZHANG Qihui WU The Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space Ministry of Industry and Information TechnologyNanjing University of Aeronautics and AstronauticsNanjing 210016China National Mobile Communications Research Laboratory Southeast UniversityNanjing 211111China

The environment of low-altitude urban airspace is complex and variable due to numerous obstacles,non-cooperative aircraft,and *** Aerial Vehicles(UAVs)leveraging environmental information to achieve three-dimension collision-free trajectory planning is the prerequisite to ensure airspace ***,the timely information of surrounding situation is difficult to acquire by UAVs,which further brings security *** a mature technology leveraged in traditional civil aviation,the Automatic Dependent Surveillance-Broadcast(ADS-B)realizes continuous surveillance of the information of ***,we leverage ADS-B for surveillance and information broadcasting,and divide the aerial airspace into multiple sub-airspaces to improve flight safety in UAV trajectory *** detail,we propose the secure Sub-airSpaces Planning(SSP)algorithm and Particle Swarm Optimization Rapidly-exploring Random Trees(PSO-RRT)algorithm for the UAV trajectory planning in law-altitude *** performance of the proposed algorithm is verified by simulations and the results show that SSP reduces both the maximum number of UAVs in the sub-airspace and the length of the trajectory,and PSO-RRT reduces the cost of UAV trajectory in the sub-airspace.

关键词： Three-dimension trajectory planning of UAV Collision avoidance Sliding window ADS-B Low-altitude urban airspace

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