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Joint relay selection and power allocation protocol for two-way relaying system

International Journal of Wireless and Mobile computing 2019年第4期17卷 349-360页

作者： Zhi, Hui Zhu, Jun Hu, Yanjun Key Lab of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei Anhui230601 China

The Joint Relay Selection and Power Allocation (JRSPA) for Amplify-and-Forward (AF) relaying (JRSPA-AF) combines Power Allocation (PA) and Relay Selection (RS) very well in Two- Way Relaying (TWR) system. In order to explore the system performance of JRSPA-AF protocol, the outage probability and Diversity-Multiplexing Trade-off (DMT) of JRSPA-AF protocol are analysed. One upper bound, two lower bounds and approximate expressions of outage probability along with the DMT are derived. Based on this, the idea of JRSPA is introduced into Decode-and- Forward (DF) relaying TWR system, and the JRSPA-DF protocol is proposed. Moreover, the exact expressions of outage probability and DMT for JRSPA-DF are derived. Simulations are developed to validate the analytical results, the results show that the approximation outage probability of JRSPA-AF can be used well to evaluate system outage probability over the entire transmission SNR region, and the analysis results of outage probability of JRSPA-DF are consistent with its simulation results. In addition, the simulation results indicate that JRSPA-DF can achieve lower outage probability than JRSPA-AF and other protocols. Copyright © 201. Inderscience Enterprises Ltd.

关键词： Probability

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Challenge-Aware RGBT Tracking 1

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1.th European Conference on Computer Vision, ECCV 2020

作者： Li, Chenglong Liu, Lei Lu, Andong Ji, Qing Tang, Jin Key Lab of Intelligent Computing and Signal Processing of Ministry of Education Anhui Provincial Key Laboratory of Multimodal Cognitive Computation School of Computer Science and Technology Anhui University Hefei230601 China

ISBN: (数字)9783030585426

ISBN: (纸本)9783030585419

RGB and thermal source data suffer from both shared and specific challenges, and how to explore and exploit them plays a critical role to represent the target appearance in RGBT tracking. In this paper, we propose a novel challenge-aware neural network to handle the modality-shared challenges (e.g., fast motion, scale variation and occlusion) and the modality-specific ones (e.g., illumination variation and thermal crossover) for RGBT tracking. In particular, we design several parameter-shared branches in each layer to model the target appearance under the modality-shared challenges, and several parameter-independent branches under the modality-specific ones. Based on the observation that the modality-specific cues of different modalities usually contains the complementary advantages, we propose a guidance module to transfer discriminative features from one modality to another one, which could enhance the discriminative ability of some weak modality. Moreover, all branches are aggregated together in an adaptive manner and parallel embedded in the backbone network to efficiently form more discriminative target representations. These challenge-aware branches are able to model the target appearance under certain challenges so that the target representations can be learnt by a few parameters even in the situation of insufficient training data. From the experimental results we will show that our method operates at a real-time speed while performing well against the state-of-the-art methods on three benchmark datasets. © 2020, Springer Nature Switzerland AG.

关键词： Computers

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RGB-T Saliency Detection via Robust Graph Learning and Collaborative Manifold Ranking 14th

RGB-T Saliency Detection via Robust Graph Learning and Colla...

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1.th International Conference on Bio-inspired computing: Theories and Applications, BIC-TA 201.

作者： Sun, Dengdi Li, Sheng Ding, Zhuanlian Luo, Bin Key Lab of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei230601 China School of Internet Anhui University Hefei230039 China

ISBN: (纸本)9789811534140

Visual saliency detection inspired by brain cognitive mechanisms is an important component of computer vision, aiming at automatically highlight salient visual objects from the image background. In complex real scenarios, integrating multiple different yet complementary feature representations has been proved to be an effective way for boosting saliency detection performance. In this paper, we propose a novel collaborative algorithm for saliency detection by adaptively incorporating information from grayscale and thermal images. Specifically, we first construct an affinity graph model via robust graph learning to characterize the feature similarities and location relationships between two different image patches under each modal. Based on these affinity graphs, a collaborative manifold ranking method cross-modality consistent constraints is designed to effectively and efficiently infer the salient score for each patch. Moreover, we introduce a weight for each modality to describe the reliability, and integrate them into the graph-based manifold ranking scheme to achieve an adaptive weighted fusion of different source data. For optimization, we propose some iterative algorithms to efficiently solve the models with several subproblems. Experiments on the grayscale-thermal datasets demonstrate the superior performance of the new method over the state-of-the-art approaches. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Graphic methods

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Dual-Graph Regularized Sparse Low-Rank Matrix Recovery for Tag Refinement 14th

Dual-Graph Regularized Sparse Low-Rank Matrix Recovery for T...

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1.th International Conference on Bio-inspired computing: Theories and Applications, BIC-TA 201.

作者： Sun, Dengdi Bao, Yuanyuan Ge, Meiling Ding, Zhuanlian Luo, Bin Key Lab of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei230601 China School of Internet Anhui University Hefei230039 China

ISBN: (纸本)9789811534140

In recent years, extremely large amounts of images with manual tags are easily available in many social websites such as Twitter, Flickr, and Instagram. However, these user-provided tags are often imprecise and incomplete, which inevitably limits the performances of image retrieval and other related applications. To this end, tag refitment technology aims at improving the quality of images tags automatically, and has been a fundamental challenge in Internet era. In this paper, we propose a novel dual-graph regularized sparse low-rank matrix recovery method, referred to as DGSLR briefly, to infer and improve the manual tags. Specifically, our DGSLR model first suppress the sparse noisy tags by norm, and decompose simultaneously the residual low-rank matrix to learning the low-dimensional vector representations of images and tags. Moreover, the visual similarities and the tag pairwise correlation are fully exploited to smooth the decomposition results by using the dual lapalcian graph regularization terms. For optimization, an improved alternative iteration strategy is designed to solve the resulting objective function. Extensive experiments on the tasks of tag refinement demonstrate the superior performance of the proposed algorithms over several representative methods, especially when the manual tag data is highly noisy and sparse. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Image enhancement

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A Novel Tri-band Frequency Selective Surface 2

A Novel Tri-band Frequency Selective Surface

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2020 2nd International Conference on Artificial Intelligence Technologies and Application, ICAITA 2020

作者： Wu, Shenbing Chen, Mingsheng Wang, Chao Wu, Xianliang Key Lab of Ministry of Education of Intelligent Computing and Signal Processing Anhui University Hefei Anhui230601 China School of Electronic Engineering Huainan Normal University Huainan Anhui232001 China

This paper presents a novel tri-band frequency miniaturized frequency selection surface (FSS). The proposed FSS consists of single-node folding and single-node folding bending. The single-layer FSS exhibits three stop bands centered at 2.45, 3.61.and 5.79 GHz, with bandwidths of 0.42, 0.48 and 0.70 GHz, respectively. The proposed FSS has better miniaturization characteristics, and its cell size is 0.1.6 ?×0.1.6 ?. The three stop band frequencies of the FSS can be independently controlled by simply changing the length of the corresponding branch. In addition, the proposed FSS is symmetrical about the center and exhibits good resonance stability in both TE and TM polarization. The prototype of the proposed FSS was fabricated and tested, compared with the simulation results, the FSS showed stable performance. This method provides ideas for designing multiband FSS in the future. © 2020 Published under licence by IOP Publishing Ltd.

关键词： Frequency selective surfaces

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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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Conference on Computer Vision and Pattern Recognition (CVPR)

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

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.

关键词：

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Wideband 1.-port mimo antenna array for 5g metal-frame smartphone applications

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Progress In Electromagnetics Research C 2020年 104卷 229-240页

作者： Liu, Peng Sun, Yufa Liu, Tao Li, Qing Wang, Xuefeng Key Lab of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei230601 China

A wideband 1.-port multiple input multiple output (MIMO) antenna array operated below 6 GHz for the fifth generation (5G) metal-frame smartphones is presented and discussed in this paper. The proposed MIMO antenna array element is composed of a microstrip line with a tuning stub and rectangular slot. The size of the rectangular slot is only 1. mm × 2 mm (0.21.λ0 × 0.028λ0, and λ0 is the wavelength with the resonance frequency of 4.2 GHz). U-shaped slots on the substrate are used to reduce the mutual coupling between the antenna elements. At the same time, in order to improve the radiation characteristics of the antenna arrays, narrow slits are etched in the metal-frame. The proposed antenna covers 3.3–5.5 GHz (S1. © 2020, Electromagnetics Academy. All rights reserved.

关键词： Antenna arrays

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A Dual-band Monopole Antenna with EBG for Wearable Wireless Body Area Networks

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Applied Computational Electromagnetics Society Journal 2021年第1期36卷 48-54页

作者： Wang, Chao Zhang, Liang Wu, Shenbing Huang, Shijie Liu, Changqing Wu, Xianliang Key Lab of Ministry of Education of Intelligent Computing & Signal Processing Anhui University Hefei City China AnHui Province Key Laboratory of Simulation and Design Electronic Information System Hefei Normal University Hefei City China

This paper proposes a dual-band wearable monopole antenna adopting an electromagnetic band-gap (EBG) structure, which operates at 2.45 and 5.8 GHz ISM bands and is suitable for wearable applications. Both the monopole antenna and the EBG structure are fabricated on an F4B semi-flexible substrate having a dielectric constant of 2.2. The EBG structure effectively isolates the human body from the radiation of the antenna and reduces the specific absorption rate (SAR) of it by more than 97.5%. This improves the antenna gain and the peak gain reaches 9.1.dBi at 5.8 GHz. The wearable performance of the antenna showed that it can sustain good performance even under realistic human body loading. Besides, the antenna has a small size, which makes it ideal for wearable applications. © ACES

关键词： Monopole antennas

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Understanding the Robustness of 3D Object Detection with Bird’s-Eye-View Representations in Autonomous Driving

arXiv

引用

arXiv 2023年

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 Dept. of Comp. Sci. and Tech. Institute for AI THBI Lab BNRist Center Tsinghua University China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education School of Computer Science and Technology Anhui University Information Materials and Intelligent Sensing Laboratory of Anhui Province China SAIC Motor AI Lab China Zhongguancun Laboratory China

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-LiDAR fusion 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. Code available at https: //***/zzj403/BEV_Robust. Copyright © 2023, The Authors. All rights reserved.

关键词： Birds

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A High Isolation UWB MIMO Antenna based on Angle Diversity

A High Isolation UWB MIMO Antenna based on Angle Diversity

引用

IEEE International Wireless Symposium (IWS)

作者： Qin Li Yufa Sun Key Lab of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei China

A UWB MIMO antenna based on angle diversity technology is proposed in this paper. This antenna integrates Vivaldi antenna and UWB slot antenna with a compact size of 261.;26mm 2 , the difference of radiation patter... 详细信息

ISBN: (数字)9781728167039

ISBN: (纸本)9781728167046

A UWB MIMO antenna based on angle diversity technology is proposed in this paper. This antenna integrates Vivaldi antenna and UWB slot antenna with a compact size of 26×26mm 2 , the difference of radiation pattern can realize lower coupling between different antenna units. Less than -1. dB isolation between different ports can be obtained through the whole UWB band (3.1.1..6GHz). In addition, the combination of one C-Shaped structure and two L-Shaped structures (CLL) avoids the interference of WLAN (5.1.5-5.825GHz) band. The proposed antenna has good performance, which is suitable for UWB communication system.

关键词： Wireless LAN Slot antennas Vivaldi antennas Interference Ultra wideband antennas MIMO communication Antenna radiation patterns

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