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European Conference on Antennas and Propagation, EuCAP

作者： Wenjie Ding Guoda Xie Yingsong Li Zhixiang Huang The Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei China Ministry of Education Center for Big Data and Population Health of IHM Anhui University Hefei China The Jianghuai Advance Technology Center Hefei China

ISBN: (数字)9788831299107

ISBN: (纸本)9798350366327

In this paper, we introduce a novel Monte Carlo wave function method (MCWFM) for simulating the transient response of Rydberg atoms under rapidly varying electric fields, aimed at high-precision electric field measurements and wireless communication reception. This approach leverages the electromagnetically induced transparency (EIT) effect and Autler- Townes (AT) splitting in Rydberg atoms, offering enhanced efficiency compared to traditional density matrix methods by focusing solely on wave function evolution, thereby reducing computational complexity. Additionally, we account for Doppler effects in AT splitting through MCWFM, providing faster results than conventional Runge-Kutta methods. This work lays a solid foundation for advancing Rydberg atom technology in the development of high-capacity, high-fidelity wireless communication systems.

关键词： Wireless communication Atomic measurements Transient response Rydberg atoms Receivers Wave functions Optical fiber communication Doppler effect Electric fields Computational complexity

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MSCA-UNet: Multi-Scale Channel Adaptive Sensing Module for Medical Image Segmentation

MSCA-UNet: Multi-Scale Channel Adaptive Sensing Module for M...

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New Trends in Computational Intelligence (NTCI), International Conference on

作者： Liangjin Diao Longfeng Shen Jiacong Chen Fangzhen Ge Mengwen Li Anhui Engineering Research Center for Intelligent Computing and Application on Cognitive Behavior (ICACB) College of Computer Science and Technology Huaibei Normal University Huaibei Anhui China Institute of Artificial Intelligence Hefei Comprehensive National Science Center Hefei China Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei Anhui China

ISBN: (数字)9798331517021

ISBN: (纸本)9798331517038

Recent advancements in CNNs for medical image segmentation have focused on the combination of CNN and Transformer architectures to capture both local and global features. However, challenges remain, such as effectively utilizing fused features at the encoder-decoder bottleneck and addressing blurred object edges in datasets. To tackle these issues, we introduce a multi-scale channel adaptive sensing module, enhancing the model's representational and perceptual capabilities by integrating multi-scale and channel-specific information. Additionally, we propose a cross-perception module and multi-scale segmentation head to improve global coordination and multi-scale information gathering. Experiments on the ACDC and Synapse datasets demonstrate our model's superiority.

关键词： Image segmentation Adaptation models Head Image edge detection Computer architecture Transformers Market research Sensors Synapses Biomedical imaging

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Near-field Source DOA Estimation Algorithm Based on De-impact Function under Impulse Noise

Near-field Source DOA Estimation Algorithm Based on De-impac...

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IEEE International Conference on Electronic Information and Communication Technology (ICEICT)

作者： Xingchao Xu Baohe Pang Yingsong Li Liping Li Dingcheng Zou Nikola Zlatanov College of Information and Communication Engineering Harbin Engineering University Harbin China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University China Faculty of Computer and Engineering Sciences Innopolis University Innopolis Russia

ISBN: (数字)9798350384437

ISBN: (纸本)9798350384444

In addressing the issue of localizing near-field source signals in the presence of impulse noise, this manuscript introduces a novel de-impact function designed for preprocessing received signals to alleviate the interference caused by impulse noise. Simulation experiments verify the effectiveness of the proposed de-impact function in effectively suppressing impulse noise. Furthermore, to augment estimation precision, a novel algorithm for near-field source localization is proposed. Building upon the framework of correlation entropy theory, a new correntropy covariance matrix is formulated to replace the original signal covariance matrix for signal processing. Through a succession of low-bias approximations between near-field and far-field scenarios, the algorithm converts the original 2-D search into 1-D operations. Additionally, the conventional spectral peak search is replaced by polynomial solving to further mitigate the computational complexity of the algorithm.

关键词： Location awareness Direction-of-arrival estimation Noise signal processing algorithms Estimation Interference Approximation algorithms

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Two-dimensional Eletrostatically Actuated MEMS Micromirror 5

Two-dimensional Eletrostatically Actuated MEMS Micromirror

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5th IEEE International Conference on Electronic Information and Communication Technology, ICEICT 2022

作者： Tao, Wei Ren, Xingang He, Shuping Wu, Xianliang Cai, Xueyuan Huang, Zhixiang Key Laboratory of Target Recognition and Feature Extraction of Anhui Province Lu'an China Ministry of Education Anhui University Key Laboratory of Intelligent Computing & Signal Processing Hefei China Anhui University Key Laboratory of Electromagnetic Environmental Sensing of Anhui Province Hefei China School of Electronic Engineering and Intelligent Manufacturing Anqing Normal University Anqing China

ISBN: (数字)9781665472111

ISBN: (纸本)9781665472111

Recently, the development of LiDAR in the field of vehicle has made the core micromirror with essential characteristics of large tilted angle and small size. We proposed a two-dimensional electrostatically actuated MEMS micromirror with a slender torsion bar. With the modified theoretical formula, two different torsional modes and corresponding torsional frequencies of the micromirror are obtained, which are then compared to the results by finite element simulation, and revealed a good agreement. The rotation angle of the micromirror is improved through optimizing the micromirror structure. Meanwhile, it is found that the driving voltage and the moment of inertia introduce the softening behavior of the spring, which will then affect the torsion frequency. To prevent the torsion bar stress is too large, with the sinusoidal driving voltage of 75V and 100V, the corresponding mechanical rotation angles are 14.8° and 15.3° at a driving frequency of 340.5Hz and 1500Hz, respectively. © 2022 IEEE.

关键词： Torsional stress

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A Relay Buffer Prediction Method Based on LSTM in Terminal Cooperative Communication

A Relay Buffer Prediction Method Based on LSTM in Terminal C...

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International Conference on Communication Technology (ICCT)

作者： Jie Fei Hui Zhi Kui Tie Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Electronic and Information Engineering Anhui University Hefei China Ceyear Technologies (AnHui) CO. LTD Bengbu China

In terminal cooperative communication, relay assisted communication with buffer has significant advantages in improving system throughput, signal-to-noise ratio, and reducing system outage probability. The existing relay methods with buffer are all fixed buffer method with a fixed size of the buffer and only considering relay wholehearted cooperation and forwarding, that is, all buffer of the relay assists communication. However, when the forwarding task is small and there is a large idle in forwarding buffer, the buffer area cannot be fully utilized. When the forwarding task is large and forwarding buffer is busy, packet loss may occur in the forwarding task. In order to improve the usage efficiency of relay buffer and reduce packet loss, this paper proposes a relay buffer prediction method based on the long short-term memory network to predict the amount of data that the relay needs to forward. According to the prediction, the size of the relay buffer is divided, so that the buffer can be dynamically adjusted on demand. Simulation results show that, compared with the fixed buffer method, the relay buffer prediction method has a better buffer usage efficiency and a lower packet loss rate.

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Distributed solving Sylvester equations with fractional order dynamics

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Control Theory and Technology 2021年第2期19卷 249-259页

作者： Songsong Cheng Shu Liang Yuan Fan Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Electrical Engineering and AutomationAnhui UniversityHefei230601AnhuiChina Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education School of Automation and Electrical EngineeringUniversity of Science and Technology BeijingBeijing100083China

This paper addresses distributed computation Sylvester equations of the form AX+XB=C with fractional order *** partitioning parameter matrices A,B and C,we transfer the problem of distributed solving Sylvester equations as two distributed optimization models and design two fractional order continuous-time algorithms,which have more design freedom and have potential to obtain better convergence performance than that of existing first order ***,rewriting distributed algorithms as corresponding frequency distributed models,we design Lyapunov functions and prove that proposed algorithms asymptotically converge to an exact or least squares ***,we validate the effectiveness of proposed algorithms by providing a numerical example.

关键词： Fractional order calculus Distributed optimization Sylvester equation Frequency distributed model Convergence

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Understanding the Robustness of 3D Object Detection with Bird'View Representations in Autonomous Driving

Understanding the Robustness of 3D Object Detection with Bir...

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2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2023

作者： Zhu, Zijian Zhang, Yichi Chen, Hai Dong, Yinpeng Zhao, Shu Ding, Wenbo Zhong, Jiachen Zheng, Shibao Institute of Image Communication and Network Engineering Shanghai Jiao Tong University China Institute for Ai Tsinghua University BNRist Center Thbi Lab Dept. of Comp. Sci. and Tech. China School of Computer Science and Technology Anhui University Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Information Materials and Intelligent Sensing Laboratory of Anhui Province China Saic Motor Ai Lab Zhongguancun Laboratory China

ISBN: (纸本)9798350301298

3D object detection is an essential perception task in autonomous driving to understand the environments. The Bird's-Eye-View (BEV) representations have significantly improved the performance of 3D detectors with camera inputs on popular benchmarks. However, there still lacks a systematic understanding of the robustness of these vision-dependent BEV models, which is closely related to the safety of autonomous driving systems. In this paper, we evaluate the natural and adversarial robustness of various representative models under extensive settings, to fully understand their behaviors influenced by explicit BEV features compared with those without BEV. In addition to the classic settings, we propose a 3D consistent patch attack by applying adversarial patches in the 3D space to guarantee the spatiotemporal consistency, which is more realistic for the scenario of autonomous driving. With substantial experiments, we draw several findings: 1) BEV models tend to be more stable than previous methods under different natural conditions and common corruptions due to the expressive spatial representations;2) BEV models are more vulnerable to adversarial noises, mainly caused by the redundant BEV features;3) Camera-LiDARfusion models have superior performance under different settings with multi-modal inputs, but BEV fusion model is still vulnerable to adversarial noises of both point cloud and image. These findings alert the safety issue in the applications of BEV detectors and could facilitate the development of more robust models. © 2023 IEEE.

关键词： Autonomous driving

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Blockchain-Assisted Revocable Cross-Domain Authentication for Vehicular Ad-Hoc Networks

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IEEE Transactions on Dependable and Secure computing 2025年

作者： Li, Ru Cui, Jie Zhang, Jing Wei, Lu Zhong, Hong He, Debiao Anhui University Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Hefei230039 China Anhui University Anhui Engineering Laboratory of IoT Security Technologies Hefei230039 China Wuhan University School of Cyber Science and Engineering 430072 China

With the rapid development of vehicular ad-hoc networks (VANETs) and the increasing diversification of user demands, interactions between different management domains have become more frequent. Identity authentication is an effective way to establish cross-domain trust and secure communication. However, the existing cross-domain authentication schemes of VANETs are limited to the same management or authentication technology for each domain and rely on centralized cross-domain identity management. Even distributed management solutions encounter latency sensitivity, security and privacy challenges. To address these challenges, we propose a blockchain-assisted revocable cross-domain authentication scheme for VANETs. The proposed scheme can establish trust between domain entities by deploying different authentication methods and using distributed management to avoid single-point failures. In addition, the scheme can revoke the identity of malicious vehicles by updating the group public key, thereby ensuring the security and privacy of cross-domain Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication. This design avoids the additional impacts of blockchain technology constraints on the high mobility and real-time requirements of VANETs. Security analysis and performance evaluation show that our scheme can resist more attacks and has better security than other related schemes while also achieving a better balance between communication and computational cost. © 2025 IEEE.

关键词： Vehicular ad hoc networks

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Conditional Generative Adversarial Defogging Algorithm Based on Polarization Characteristics 33

Conditional Generative Adversarial Defogging Algorithm Based...

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第33届中国控制与决策会议

作者： Jingjing Zhang Kangsheng Bao Xin Zhang Fudong Nian Teng Li Yuzhou Zeng Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education (Anhui university) Key Laboratory of Polarized Light Imaging and Detection Technology in Anhui Province Hefei No.6 High School Hefei University

ISBN: (纸本)9781665431293

To overcome image degradation under the conditions of haze,and fog,a method using conditional generative adversarial defogging algorithm based on polarization characteristic is *** original images with different polarization angles were obtained from the original image,and then the polarization images were characterized using Stokes *** the relationship between Stokes vector and polarization image,each polarization image with different angles is input into the same network to extract *** the same time,the enhanced network is used to extract the characteristics of the fog area in the polarization image,and the polarization information is extracted by layer jump connection,which is fused with the image features of different *** constructing the loss function and obtaining the optimal solution,the fog-free image is finally *** results show that a clear image can be reconstructed in fog situations by using conditional generative adversarial network-based on polarization characteristics,and the structural similarity is improved by about 10%,the peak signal to noise ratio is increased by about 0.5.

关键词： polarization characteristics conditional generative adversarial network image processing image defogging feature fusion enhanced network

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Unknown Type Streaming Feature Selection via Maximal Information Coefficient

Unknown Type Streaming Feature Selection via Maximal Informa...

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IEEE International Conference on Data Mining Workshops (ICDM Workshops)

作者： Peng Zhou Yunyun Zhang Yuanting Yan Shu Zhao Key Laboratory of Intelligent Computing and Signal Processing (the Ministry of Education of China) School of Computer Science and Technology Anhui University Hefei China

Feature selection aims to select an optimal minimal feature subset from the original datasets and has become an indispensable preprocessing component before data mining and machine learning, especially in the era of big data. Most feature selection methods implicitly assume that we can know the feature type (categorical, numerical, or mixed) before learning, then design corresponding measurements to calculate the correlation between features. However, in practical applications, features may be generated dynamically and arrive one by one over time, which we call streaming features. Most existing streaming feature selection methods assume that all dynamically generated features are the same type or assume we can know the feature type for each new arriving feature on the fly, but this is unreasonable and unrealistic. Therefore, this paper firstly studies a practical issue of Unknown Type Streaming Feature Selection and proposes a new method to handle it, named UT-SFS. Extensive experimental results indicate the effectiveness of our new method. UT-SFS is nonparametric and does not need to know the feature type before learning, which aligns with practical application needs.

关键词： Measurement Microwave integrated circuits Correlation Conferences Machine learning Big Data Feature extraction

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