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Antennas and Propagation & USNC/URSI National Radio Science Meeting

作者： Yinfeng Xia Yingsong Li Wei Xue Luyu Zhao Eugene Sinkevich Vladimir Mordachev College of Information and Communication Engineering Harbin Engineering University Harbin China The Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University China EMC R&D laboratory Belarusian State University of Informatics and Radioelectronics Minsk Belarus

ISBN: (数字)9798350369908

ISBN: (纸本)9798350369915

A passive component incorporated miniaturization super-wideband (PCIM-SWB) antenna is proposed for EMC measurement, which has a feeding line with passive components, circle-shaped radiating patch, defected ground. The proposed PCIM-SWB antenna is created from a simple monopole, where its defected ground is to enhance its bandwidth. The two passive components are integrated into the feeding to further to improve its bandwidth to cover lower frequency band. By co-simulation and optimization using HFSS and ADS, a -10 dB fractional bandwidth of 163.2% is gotten for the PCIM-SWB ranging from 0.48 GHz to 4.74 GHz with omnidirectional radiating pattern, which can be employed for Wi-Fi and many military applications.

关键词： Antenna measurements Bandwidth Electromagnetic compatibility Distance measurement Broadband antennas Antenna accessories Wireless fidelity

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Accepted Influence Maximization under Linear Threshold Model on Large-Scale Social Networks

Accepted Influence Maximization under Linear Threshold Model...

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IEEE International Conference on Trust, Security and Privacy in computing and communications (TrustCom)

作者： Xiaojuan Yang Jiaxing Shang Linjiang Zheng Dajiang Liu Shu Fu Baohua Qiang Key Laboratory of Dependable Service Computing in Cyber Physical Society Ministry of Education College of Computer Science Chongqing University Chongqing China School of Microelectronics and Communication Engineering Chongqing University Chongqing China Guangxi Key Laboratory of Trusted Software Guilin University of Electronic Technology Guilin China

ISBN: (纸本)9781665416597

The influence maximization (IM) problem, which aims to find $k$ most influential individuals from a social network to maximize the influence spread, has been extensively studied. Existing works all rely on the assumption that influenced individuals will definitely try to propagate the information to their neighbors through social trust. However, in real-world this assumption can be over-simplistic since trust-levels among different individuals usually exhibit high diversity. As a result, an influenced individual may choose not to further propagate the information to his neighbors. Motivated by the observation, in this paper we propose a new accepted influence maximization (AIM) problem where the influenced individuals are further divided into two subgroups, i.e., accepted and active, where only active individuals will continue to propagate the information. We prove this problem is NP-hard and the objective function is submodular, based on which a greedy algorithm is proposed with ( $1-1/e-\epsilon$ ) approximation guarantee. Considering the low computational efficiency of the greedy algorithm, we further propose a scalable path-based algorithm ALDAG. We conduct experiments on real datasets and the results demonstrate the effectiveness and efficiency of our method.

关键词： Greedy algorithms Data privacy Social networking (online) Computational modeling Heuristic algorithms Linear programming Approximation algorithms

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High Degree of Freedom Low Coupling Sparse MIMO Array

High Degree of Freedom Low Coupling Sparse MIMO Array

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

作者： Yichang Yao Baohe Pang Yingsong Li Canping Yu Wudang Xiao Liping Li 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

To achieve high precision direction-of-arrival estimation of MIMO arrays in highly coupled environments, based on the difference and cooperative array principles, the uniform array fitted with 5 base layer array and the uniform array fitted with 6 base layer array were used as transmitting arrays, and with the addition of 1 base layer layer sparse array as receiving array, two sparse multi-in multiple-out arrays were designed for single-base radar, which have the characteristics of low coupling of transmitting array and high freedom of receiving array.

关键词： Couplings Direction-of-arrival estimation Accuracy Target recognition Fitting Estimation Radar

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Matrix Classifier On Dynamic Functional Connectivity For Mci Identification

Matrix Classifier On Dynamic Functional Connectivity For Mci...

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IEEE International Conference on Image Processing

作者： Lei Zhou Liang Zhang Xiao Bai Jun Zhou School of Computer Science and Engineering Beijing Advanced Innovation Center for Big Data and Brain Computing State Key Laboratory of Software Development Environment Beihang University Beijing School of Information and Communication Technology Griffith University Nathan

ISBN: (数字)9781728163956

ISBN: (纸本)9781728163963

One of the most popular method for Alzheimer's disease (AD) diagnosis is exploring the Brain functional connectivity (FC) from resting-state functional magnetic resonance imaging (RS-fMRI). To early prevent AD, it is crucial to distinguish AD and and its preclinical stage, mild cognitive impairment (MCI) and early MCI (eMCI). In many existing works, dynamic functional connectivity (dFC) which contains rich spatiotemporal information has been exploited for the MCI and eMCI identification. However, most of these dFC based methods only consider the correlation between discrete brain status while ignore the valuable spatiotemporal information contained in dFC. To overcome this limitation, we propose a matrix classifier based method on the dFC signal for MCI and eMCI identification. Specifically, we first represent the dFC correlations by matrix features which contain rich spatiotemporal information and then learn the support matrix machines (SMM) to classify AD and its preclinical stage. Experiments on 600 real people data provide by the Alzheimer's Disease Neuroimaging Initiative (ADNI) demonstrate that our proposed matrix classifier based method outperforms other FC and dFC based methods for both normal controls (NC)/MCI identification and NC/eMCI identification.

关键词： Feature extraction Correlation Dementia Microsoft Windows Spatiotemporal phenomena Training

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Speaker recognition with mel scale-based wavelet packet decomposition and AR-volterra model

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ICIC Express Letters, Part B: Applications 2016年第10期7卷 2087-2094页

作者： Yang, Shuying Guo, Jijn Jiang, Jiaojiao School of Computer and Communication Engineering Tianjin University of Technology No. 391 Binshui Xidao Xiqing District Tianjin300384 China Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology No. 391 Binshui Xidao Xiqing District Tianjin300384 China

In order to improve the rate of speaker recognition, this paper proposes a new scheme with Mel scale-based Wavelet Packet Decomposition and AR-Volterra model. First, the speech signal is decomposed by wavelet packet of Mel scale, and calculate energy spectrum of the sub-band signals. The sub-bands of low energy are discarded according to weighting the proportion ofenergy for all-bands. Second, chaos ofsub-band signals are determined by the largest Lyapunov exponent. Ifsub-band is chaotic, Volterra adaptive model will be used to extract features. Otherwise, the autoregressive model will be used to extract features. Third, linear and nonlinear characteristic parameters will be used to speaker recognition. Hidden Markov model is used to recognize speaker. The experimental results show the extracted features have been obviously improved. © 2016 ICIC International.

关键词： Hidden Markov models

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REVERSIBLE DATA HIDING IN ENCRYPTED IMAGE BASED ON BLOCK HISTOGRAM SHIFTING

REVERSIBLE DATA HIDING IN ENCRYPTED IMAGE BASED ON BLOCK HIS...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Zhaoxia Yin Andrew Abel Xinpeng Zhang Bin Luo School of Communication and Information Engineering Shanghai University Shanghai 200072 P.R. China. Computing Science and Mathematics University of Stirling. Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei 230601 P.R. China.

ISBN: (纸本)9781479999897

Since there is good potential for practical applications such as encrypted image authentication, content owner identification and privacy protection, reversible data hiding in encrypted image (RDHEI) has attracted increasing attention in recent years. In this paper, we propose and evaluate a new separable RDHEI framework. Additional data can be embedded into a cipher image previously encrypted using Josephus traversal and a stream cipher. A block histogram shifting (BHS) approach using self-hidden peak pixels is adopted to perform reversible data embedding. Depending on the keys held, legal receivers can extract only the embedded data with the data hiding key, or, they can decrypt an image very similar to the original with the decryption key. They can extract both the embedded data and recover the original image error-free if both keys are available. The results demonstrate that higher embedding payload, better quality of decrypted-marked image and error-free image recovery are achieved.

关键词： Signal processing in encrypted domain (SPED) Reversible data hiding in encrypted images (RDHEI) Privacy protection Hidden data images keys keys Cays Imagery (Psychotherapy) embedding Image Error-free operations Locks

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High-contrast transparency comb of the electromagnetically-induced-transparency memory

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Physical Review A 2018年第3期98卷 033802-033802页

作者： Sheng-Jun Yang Jun Rui Han-Ning Dai Xian-Min Jin Shuai Chen Jian-Wei Pan Hefei National Laboratory for Physical Sciences at Microscale and Department of Modern Physics University of Science and Technology of China Hefei Anhui 230026 China CAS Center for Excellence and Synergetic Innovation Center in Quantum Information and Quantum Physics University of Science and Technology of China Hefei Anhui 230026 China CAS-Alibaba Quantum Computing Laboratory Shanghai 201315 China State Key Laboratory of Advanced Optical Communication Systems and Networks School of Physics and Astronomy Shanghai Jiao Tong University Shanghai 200240 China

Quantum interface of coherent optical field and atomic excitations plays an important role in quantum metrology and quantum information science. The electromagnetically-induced-transparency (EIT) technique has shown versatile and powerful capability in many applications during the last decades. By using efficient EIT-based memory, we directly observed single-photon-level Ramsey interference and also high-contrast spectral transparency comb with a visibility up to about 0.81 at around the resonant line in cold atoms. The interference fringes are mainly influenced by the pulse repetition period, the waveform overlap of the slowed and retrieved signal pulses, and the coherent lifetime of the EIT memory. All these factors have been investigated in detail. Such high-contrast interference fringe may offer us methods for precision measurement and potential applications in areas of atomic clock and magnetometry.

关键词： Atom interferometry Coherent control Cooling & trapping Light-matter interaction Quantum optics

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Wireless Large AI Model: Shaping the AI-Native Future of 6G and Beyond

arXiv

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arXiv 2025年

作者： Zhu, Fenghao Wang, Xinquan Li, Xinyi Zhang, Maojun Chen, Yixuan Huang, Chongwen Yang, Zhaohui Chen, Xiaoming Zhang, Zhaoyang Jin, Richeng Huang, Yongming Feng, Wei Yang, Tingting Bai, Baoming Gao, Feifei Yang, Kun Liu, Yuanwen Muhaidat, Sami Yuen, Chau Huang, Kaibin Wong, Kai-Kit Niyato, Dusit Debbah, Mérouane College of Information Science and Electronic Engineering Zhejiang University Hangzhou310027 China School of Automation Southeast University Nanjing210096 China Tsinghua University Beijing100084 China Pengcheng Laboratory Shenzhen518066 China State Key Laboratory of Integrated Service Networks Xidian University Xi’an710071 China State Key Laboratory of Novel Software Technology Nanjing University Nanjing210008 China Suzhou215163 China The University of Hong Kong Hong Kong KU 6G Research Center Computer and Communication Engineering Khalifa University Abu Dhabi127788 United Arab Emirates School of Electrical and Electronic Engineering Nanyang Technological University Singapore Singapore Department of Electronic and Electrical Engineering University College London LondonWC1E 7JE United Kingdom College of Computing and Data Science Nanyang Technological University Singapore639798 Singapore KU 6G Research Center Department of Computer and Information Engineering Khalifa University Abu Dhabi127788 United Arab Emirates

The emergence of sixth-generation and beyond communication systems is expected to fundamentally transform digital experiences through introducing unparalleled levels of intelligence, efficiency, and connectivity. A promising technology poised to enable this revolutionary vision is the wireless large AI model (WLAM), characterized by its exceptional capabilities in data processing, inference, and decision-making. In light of these remarkable capabilities, this paper provides a comprehensive survey of WLAM, elucidating its fundamental principles, diverse applications, critical challenges, and future research opportunities. We begin by introducing the background of WLAM and analyzing the key synergies with wireless networks, emphasizing the mutual benefits. Subsequently, we explore the foundational characteristics of WLAM, delving into their unique relevance in wireless environments. Then, the role of WLAM in optimizing wireless communication systems across various use cases and the reciprocal benefits are systematically investigated. Furthermore, we discuss the integration of WLAM with emerging technologies, highlighting their potential to enable transformative capabilities and breakthroughs in wireless communication. Finally, we thoroughly examine the high-level challenges hindering the practical implementation of WLAM and discuss pivotal future research directions. Copyright © 2025, The Authors. All rights reserved.

关键词： Sorting

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Edge-Preserving Multi-Exposure Fusion with Guided Filtering for Structural Patch Decomposition

Edge-Preserving Multi-Exposure Fusion with Guided Filtering ...

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

作者： Yang Zhen Junwei Qi Yingsong Li College of Information and Communication Engineering Harbin Engineering University Harbin China College of Computer Science and Technology Harbin Engineering University Harbin China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei China

Multi-exposure image fusion (MEF) is one of the effective ways to obtain high dynamic range (HDR) images. Multi-scale structural patch decomposition based MEF(MSPD) and edge-preserving structural patch decomposition (MESPD) have achieved state-of-the-art fusion quality. MESPD incorporates edge-preserving factors into MSPD to preserve details in a single-scale setting. However, we find that the edge-preserving factors put too much emphasis on the edge, resulting in artifacts on some edges and loss of details. To tackle this issue, guided filter is introduced into MSPD, which is directly used as an edge-preserving filter instead of mean filter to implicitly decompose images. In addition, we have designed a flexible adaptive weight, which can further maintain details of the light and dark areas. Likewise, we inherit MESPD and MSPD to extend our method to multi-scale framework. Extensive experimental results demonstrate our method can produce satisfactory results in both static and dynamic scenes with fewer artifacts and low computational cost.

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Interactive reflection simulation via physical shading model and fast environment mapping

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ICIC Express Letters, Part B: Applications 2016年第2期7卷 351-356页

作者： Xu, Jie Fu, Jinhua School of Software Zhengzhou University of Light Industry China School of Computer and Communication Engineering Zhengzhou University of Light Industry No. 5 Dongfeng Road Zhengzhou China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou Information Science and Technology Institute Zhengzhou China

In order to enhance realistic reflection effects on some objects and realize faster rendering to meet interactive requirements, we present a novel method to produce interactive reflection simulation using physical shading model and fast environment mapping. The physical shading model could efficiently express ambient lighting, specular lighting and diffuse lighting. Also the model is based on the microfacet distribution function, which can describe physics-based characteristics. Fast environment mapping is realized by Spherical Harmonics (SH) transformation, and the rendering equation can be rewritten as a simple dot product of SH coefficients, which fits for GPU (Graphics Processing Unit) computation. The results show that we can realize faster rendering and acquire realistic reflection effects such as glossy and mapping scene on the surface. © 2016 ICIC International.

关键词： Lighting

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