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Design and Analysis of Spatial Modulation Based Orthogonal Time Frequency Space System

China communications 2021年第8期18卷 209-223页

作者： Yingchao Yang Zhiquan Bai Ke Pang Piming Ma Haixia Zhang Xinghai Yang Dongfeng Yuan Shandong Provincial Key Lab.of Wireless Communication Technologies School of Information Science and EngineeringShandong UniversityQingdao 266237China Shandong Provincial Key Lab.of Wireless Communication Technologies School of Control Science and EngineeringShandong UniversityJinan 250061China College of Information Science and Technology Qingdao University of Science and TechnologyQingdao 266061China

In this paper,we design a spatial modulation based orthogonal time frequency space(SMOTFS)system to achieve improved transmission reliability and meet the high transmission rate and highspeed demands of future mobile communications,which fully utilizes the characteristics of spatial modulation(SM)and orthogonal time frequency space(OTFS)*** detailed system design and signal processing of the SM-OTFS system have been *** closed-form expressions of the average symbol error rate(ASER)and average bit error rate(ABER)of the SM-OTFS system have been derived over the delay-Doppler channel with the help of the union bounding technique and moment-generating function(MGF).Meanwhile,the system complexity has been *** results verify the correctness of the theoretical ASER and ABER analysis of the SM-OTFS system in the high signal-to-noise ratio(SNR)regions and also show that the SM-OTFS system outperforms the traditional SM based orthogonal frequency division multiplexing(SM-OFDM)system with limited complexity increase under mobile conditions,especially in high mobility scenarios.

关键词： orthogonal time frequency space(OTFS) spatial modulation based OTFS(SM-OTFS) delay-Doppler domain average symbol error rate(ASER) average bit error rate(ABER)

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A Multi-Scale SAR-Optical Image Matching Method Using Structure-Enhanced Convolutional Layer and Transformer-CNN Model

A Multi-Scale SAR-Optical Image Matching Method Using Struct...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Yijun Liu Jie Long Qian Liu Chang Liu Qingsong Wang School of Electronics and Communication Engineering Shenzhen Campus of Sun Yatsen University Shenzhen China Beijing Institute of Control and Electronic Technology Beijing China

ISBN: (数字)9798350360325

ISBN: (纸本)9798350360332

Due to the geometric and nonlinear radiometric differences (NRD) between SAR and optical images, coupled with the impact of speckle noise, achieving robust and high-precision matching between them remains challenging. This paper introduces a novel multi-scale SAR-optical image matching method, which employs an improved multi-scale matching strategy. Specifically, we first establish an image pyramid and detect geometric keypoints of the images, subsequently segmenting the images into sub-blocks centered around these keypoints. These sub-blocks are then fed into the proposed siamese feature description network, comprising of a structure-enhanced convolutional layer and a Transformer-CNN model, for feature descriptors extraction, followed by feature matching. Finally, the matching point pairs are obtained by combining the matching relationships between image pairs of different scales. Experimental results show that our proposed algorithm achieves better matching performance compared to the existing state-of-the-art algorithms.

关键词： Image matching Speckle Optical fiber networks Feature extraction Transformers Optical imaging Radiometry

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On Interval Perturbation of the ɑ-Symmetric Implicational Algorithm 2nd

On Interval Perturbation of the ɑ-Symmetric Implicational A...

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2nd International Conference on Artificial Intelligence Logic and Applications, AILA 2022

作者： Tang, Yiming Han, Jianghui Bao, Guangqing Chen, Rui Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine School of Computer and Information Hefei University of Technology Anhui Hefei230601 China Engineering Research Center of Safety Critical Industry Measure and Control Technology Ministry of Education Hefei University of Technology Anhui Hefei230601 China

ISBN: (纸本)9789811975097

Perturbation is an important property of fuzzy reasoning algorithms. It is an important task to estimate the upper and lower bounds of the output after a perturbation (such as an interval perturbation) is given to the input. In this study, the interval perturbation problem of a fuzzy reasoning algorithm, i.e., the ɑ-symmetric implicational algorithm, is researched systematically. For FMP (Fuzzy Modus Ponens) and FMT (Fuzzy Modus Tollens) problems of fuzzy reasoning, aiming at the case of a single rule, the estimation for the upper and lower bounds are obtained for the input interval disturbance, in which R-implications and (S, N)-implications are mainly employed. Then the stability is verified on account of the upper and lower bounds. Following that, for the multi-rule case, the upper and lower bounds of the output are also given, and the corresponding stability is validated. In conclusion, it is found that the ɑ-symmetric implicational algorithm has good stability. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Fuzzy inference

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Analysis of Visual Effects Configuration Scheme for Small Cultural Complex 2

Analysis of Visual Effects Configuration Scheme for Small Cu...

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2nd IEEE International Conference on Information technology, Big Data and Artificial Intelligence, ICIBA 2021

作者： Sun, Chang Su, Zhibin Liu, Wei Ren, Hui School of Information and Communication Engineering Communication University of China Beijing China Key Laboratory of Acoustic Visual Technology and Intelligent Control Ministry of Culture and Tourism School of Information and Communication Engineering Beijing China

ISBN: (纸本)9781665428767

Stage lighting design is an important step in the visual effect configuration scheme of small cultural complex. This paper mainly discusses the lighting configuration of small space with multi-functional art services under different modes such as performance, conference, exhibition, reading and folk customs. Focusing on the analysis of lighting layout methods in drama and artistic performances, this paper takes the drama performing environment as the representative. Through the corresponding subjective evaluation experiments, research and data analysis are carried out on the lamps and lighting methods adopted in the performance. Furthermore, the optimal configuration effect of front light and top light under given constraints is selected. The research provides an effective reference for the lighting configuration of small cultural complexes, which has certain application value and practical significance. © 2021 IEEE.

关键词： Lighting

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A Singing Formant Extraction Method Based on Peak Fitting

A Singing Formant Extraction Method Based on Peak Fitting

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Culture-Oriented Science and technology (CoST), International Conference on

作者： Jingyu Liu Jiawei Wu Wei Jiang State Key Laboratory of Media Convergence and Communication (Communication University of China) China Key Laboratory of Acoustic Visual Technology and Intelligent Control SystemMinistry of Culture and Tourism (Communication University of China) China School of Information and Communication Engineering (Communication University of China) China

ISBN: (数字)9798350380347

ISBN: (纸本)9798350380354

Analyzing the timbre characteristics of different singing genres is an important issue in the field of singing acoustics. Formants are an important characteristic parameter for timbre perception, but classical acoustic formant extraction methods lack accuracy and applicability in the analysis of singing genres. In order to solve the problem of insufficient accuracy and applicability of singing formants in singing genre analysis, this paper proposes a singing formant extraction method based on peak fitting. The paper summarizes the theory and methods of extracting vocal formants and based on a large amount of experimental data analysis, proposes a vocal formant feature extraction method based on peak fitting; The effectiveness of the singing formant extraction method based on peak fitting was verified through comparative experiments with existing formant algorithms. This article provides new research ideas and methods for extracting acoustic features in singing.

关键词： Accuracy Fitting Education Feature extraction Acoustics Resonance Classification algorithms

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Design of Orthogonal Polyphase Codes for MIMO Radar Using an Enhanced Salp Swarm Algorithm 1

Design of Orthogonal Polyphase Codes for MIMO Radar Using an...

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1st International Conference on Intelligent Manufacturing and Cloud Computing, ICIMCC 2024

作者： Pang, Yu Zhao, Runhui Wen, Hong Wang, Yongfeng Feng, Xuewei Tang, Tao Zhao, Ziang Ma, Wendi School of Aeronautics and Astronautics University of Elec.Science and Tech. of China Chengdu611731 China Aircraft Swarm Intelligent Sensing and Cooperative Control Key Lab. of Sichuan Province UESTC 611731 China Intelligent IoT Communication Technology Engineering Research Center of Sichuan Province UESTC 611731 China

ISBN: (纸本)9781643685779

This paper presents the design of highly orthogonal waveforms focusing on minimizing autocorrelation sidelobes and cross-correlation peaks. An enhanced Salp Swarm Algorithm is proposed to improve global search capabilities through refined population initialization and leader position updates. The feasibility and benefits of this approach are demonstrated through practical implementation. © 2025 The Authors.

关键词： MIMO radar

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Signal Detection Method Based on Social Relationship Strength in Vehicular Ad-hoc Networks ⁎

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IFAC-PapersOnLine 2024年第10期58卷 176-181页

作者： Yi Li Shuangshuang Han Yongqiang Bai Fei-Yue Wang School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China and Key Laboratory of Ocean Observation Technology MNR Tianjin China School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China and Beijing Huairou Academy of Parallel Sensing Beijing China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

In the case of scarce communication resources, the importance of different vehicle communication levels is self-evident. They not only affect the efficiency of information exchange between vehicles and driving safety, but also directly affect the rational allocation and utilization of communication resources. Therefore, this paper proposes a signal detection method based on vehicle social relationship strength (SRS) in vehicular ad-hoc networks (VANETs) scenario, and integrates the SRS information into the data to be transmitted. In this method, minimum mean square error (MMSE) signal detection algorithm is selected for simulation, and Rayleigh channel and Rician channel are selected for simulation scenarios. This method makes full use of the intensity of social relationship between vehicles, and realizes the efficient transmission of data and the accurate transmission of communication level. Experimental verification shows that the method performs well in the VANETs scenario, and provides a new communication method for intelligent transportation, social network and other applications, which is expected to promote the technical progress and application development in related fields.

关键词： VANETs Social relation strength Image data transmission MMSE detection Intelligent transportation Social networking

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Adaptive Differentially Private Robust Federated Learning Against Backdoor Attacks 1

Adaptive Differentially Private Robust Federated Learning Ag...

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1st International Conference on Intelligent Manufacturing and Cloud Computing, ICIMCC 2024

作者： Yao, Ruixiang Wen, Hong Hou, Wenjing Ma, Wendi Sun, Fan Zhao, Ziang School of Aeronautics and Astronautics University of Elec.Science and Tech. of China Chengdu611731 China Aircraft Swarm Intelligent Sensing and Cooperative Control Key Lab. of Sichuan Province UESTC 611731 China Intelligent IoT Communication Technology Engineering Research Center of Sichuan Province UESTC 611731 China

ISBN: (纸本)9781643685779

In federated learning systems, malicious attackers can manipulate training datasets by injecting backdoor triggers to achieve data poisoning. Addressing this vulnerability, this paper proposes a new defense method, the adaptive differential privacy stochastic gradient descent (ADP-SGD) algorithm, which increases the Euclidean distance between malicious and benign updates to enhance aggregation efficiency. Experiments were conducted on typical datasets, and the results show that combining ADP-SGD with the m-Krum aggregation algorithm can effectively defend against backdoor attacks in complex attack environments. While ensuring the accuracy of the main task, it significantly reduces the success rate of backdoor attacks, especially under the condition of unknown proportions of malicious participants, proving to be effective and robust. © 2025 The Authors.

关键词： Federated learning

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Survey on Foundation Models for Prognostics and Health Management in Industrial Cyber-Physical Systems

IEEE Transactions on Industrial Cyber-Physical Systems

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IEEE Transactions on Industrial Cyber-Physical Systems 2024年 2卷 264-280页

作者： Liu, Ruonan Zhang, Quanhu Han, Te Yang, Boyuan Zhang, Weidong Yin, Shen Zhou, Donghua Shanghai Jiao Tong University Department of Automation Shanghai200240 China Tianjin University College of Intelligence and Computing Tianjin300350 China Beijing Institute of Technology Center for Energy and Environmental Policy Research Beijing100081 China Beijing Institute of Technology School of Management Beijing100081 China Beijing Laboratory for System Engineering of Carbon Neutrality Beijing100081 China Nanjing University Center for Advanced Control and Smart Operations Suzhou215163 China Hainan University School of Information and Communication Engineering Haikou570228 China Shanghai Jiaotong University Department of Automation Shanghai200240 China Norwegian University of Science and Technology Trondheim7491 Norway

Industrial Cyber-Physical Systems (ICPS) integrating disciplines such as computer science, communication technology, and engineering, have become a crucial component of modern manufacturing and industry. However, ICPS faces numerous challenges during long-term operation, including equipment faults, performance degradation, and security threats, etc. To achieve efficient maintenance and management, prognostics and health management (PHM) has been widely applied in the critical tasks of ICPS such as fault prediction, health monitoring, and maintenance decision-making. The emergence of large-scale foundation models (LFMs) like BERT and GPT marks a significant advancement in artificial intelligence (AI) technology, demonstrating substantial application potential in multiple fields. The accumulation of AI technology, rapid development of LFMs, and the abundance of industrial data and industrial process knowledge provide the foundational conditions for the construction and advancement of industrial LFMs. However, there is currently a lack of consensus on applying LFMs of PHM in ICPS, necessitating a systematic review and roadmap to clarify future development directions. To bridge this gap, this survey provides a comprehensive survey and understanding of the recent advances in LFMs of PHM in ICPS. It provides valuable references for decision makers and researchers in the industry, and helps to further improve the reliability, availability and safety of ICPS. © 2023 IEEE.

关键词： Cyber Physical System

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Self-supervised Visual Odometry Based on Geometric Consistency

Self-supervised Visual Odometry Based on Geometric Consisten...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Rujun Song Jiaqi Liu Kaisheng Liao Zhuoling Xiao Bo Yan School of Information and Communication Engineering University of Electronic Science and Technology of China Science and Technology on Electronic Information Control Laboratory Chengdu China

Learning-based monocular visual odometry (VO) has lately drawn significant attention for its robustness to camera parameters and environmental variations. Unlike most self-supervised learning-based methods, our approach simultaneously focuses on the adjacent and interval co-visibility correspondence to improve the pose estimation. To handle different pixel displacements, we apply the Multi-scale Feature Fusion component for the full exploration of latent motion features. Besides, the Interval Feature Guided Refinement component is incorporated to adaptively exploit the continuity of camera motions and steer the network for retaining pose consistency in the time domain. Extensive experiments on the KITTI and Malaga datasets have demonstrated the promising performance of our approaches. The proposed method produces competitive results against classic algorithms and outperform state-of-the-art methods by up to 23.9 % and 15.4 % on average translational and rotational evaluation.

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