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arXiv 2022年

作者： Liu, Zhengyi Tan, Yacheng He, Qian Xiao, Yun Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei China Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Artificial Intelligence Anhui University Hefei China

Convolutional neural networks (CNNs) are good at extracting contexture features within certain receptive fields, while transformers can model the global long-range dependency features. By absorbing the advantage of transformer and the merit of CNN, Swin Transformer shows strong feature representation ability. Based on it, we propose a cross-modality fusion model, SwinNet, for RGB-D and RGB-T salient object detection. It is driven by Swin Transformer to extract the hierarchical features, boosted by attention mechanism to bridge the gap between two modalities, and guided by edge information to sharp the contour of salient object. To be specific, two-stream Swin Transformer encoder first extracts multi-modality features, and then spatial alignment and channel re-calibration module is presented to optimize intra-level cross-modality features. To clarify the fuzzy boundary, edge-guided decoder achieves inter-level cross-modality fusion under the guidance of edge features. The proposed model outperforms the state-of-the-art models on RGB-D and RGB-T datasets, showing that it provides more insight into the cross-modality complementarity ***://***/liuzywen/SwinNet © 2022, CC0.

关键词： Convolutional neural networks

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Optical and Electrical Analysis of an Advanced 4T All-perovskite Tandem Solar Cell

Optical and Electrical Analysis of an Advanced 4T All-perovs...

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Progress in Electromagnetic Research Symposium (PIERS)

作者： Zhaosheng Xia Xingang Ren Shengyang Wei Zhixiang Huang Information Materials and Intelligent Sensing Laboratory of Anhui Province Institute of Physical Science and Information Technology Anhui University Hefei China Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei China

ISBN: (数字)9798350375909

ISBN: (纸本)9798350375916

The investigation of the optoelectronic characteristics of all-perovskite tandem solar cells holds pivotal significance in surpassing the Shockley-Queisser limit of single-junction perovskite solar cells. Initially, we established two distinct four-terminal tandem solar cells (4T TSCs) composed of different perovskite materials: FA 0.8 Cs 0.2 Pb(I 0.7 Br 0.3 ) 3 (E g = 1.75 eV) and MASnI 3 (E g = 1.3 eV). Through numerical simulations of the optoelectronic characteristics of 4T TSCs, we evaluated the performance of the TSCs at varying perovskite layer thicknesses. Following optimization, the power conversion efficiency (PCE) of the 4T TSCs increased from the initial 30.34% to 33.54%. Through an in-depth analysis of the cell and energy distribution in TSCs, it was observed that the light-coupling layer significantly influenced the PCE of the 4T TSCs. Upon optimizing the light-coupling layer, the PCE of the TSC increased from the initial 30.34% to 34.7%. This study provides crucial theoretical and experimental foundations for optimizing the performance of all-perovskite TSCs.

关键词： Photovoltaic cells Numerical simulation Perovskites Optical coupling Optical materials Power conversion Electromagnetics

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Affine-Projection Maximum Asymmetric Correntropy Criterion Algorithm Under System Identifications

Affine-Projection Maximum Asymmetric Correntropy Criterion A...

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International Conference on Computer Science and Network Technology (ICCSNT)

作者： Yan Peng Xinqi Huang Canping Yu Qi Mao Yingsong Li 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

The Affine-Projection Maximum Asymmetric Correntropy Criterion (APMACC) is constructed, drawing upon the fundamental principles of the maximum asymmetric correntropy criterion and an affine-projection scheme. The APMACC algorithm incorporates the asymmetric Gaussian model as a kernel function within the Affine-Projection (AP) algorithm framework, thereby endowing it with robustness against asymmetrically distributed noise. Furthermore, the bound for step-size is established in the literature. Simulation results demonstrate that the APMACC has fast convergence and low steady-state.

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Complex-valued cross-domain few-shot learning network for PolSAR image classification

Complex-valued cross-domain few-shot learning network for Po...

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IET International Radar Conference (IRC 2023)

作者： Yice Cao Dayi Zhu Zhenhua Wu Jie Chen Zhixiang Huang Lixia Yang Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education School of Electronics and Information Engineering Anhui University Hefei 230601 People's Republic of China

ISBN: (数字)9781837240982

Gathering reliable lab.led samples for polarimetric synthetic aperture (PolSAR) image classification is lab.rious. Moreover, applying a trained classifier to new domains often leads to noticeable performance degradation due to domain disparities. Therefore, this paper proposes the novel complex-valued cross-domain (CD) few-shot learning classification (CCFSLC) method for PolSAR images to address these issues. Firstly, the transferrable knowledge learning module (TKLM) with a complex-valued feature encoder (CVFE) is trained using source data with sufficient lab.led samples. Then, the deep few-shot learning module (DFSLM), constructed using the pre-trained CVFE, is trained by episodes in both source and target domains, with only minimal target lab.led samples. Meanwhile, the adversarial domain adaptation module (ADAM) is employed to eliminate domain shift. The proposed CCFSLC mainly focuses on exploring discriminative information from raw PolSAR data, while reducing the domain gap to recognize novel categories in unseen domains with only a few annotated samples. Experiments on typical PolSAR datasets validate the effectiveness of the proposed method.

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Adaptive Step-Size Sparse Millimeter Wave Imaging Algorithm Based on Approximate Observations

Adaptive Step-Size Sparse Millimeter Wave Imaging Algorithm ...

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International Conference on Computer Science and Network Technology (ICCSNT)

作者： Dianhao Wang Xinqi Huang Canping Yu Qi Mao Yingsong Li 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

The currently constructed millimeter wave imaging system has the problems of long sampling time and more sampling points of antenna units, and the use of compressed perception algorithm can improve the imaging quality when the number of sampling points are much smaller than the Nyquist distance sampling. The traditional compressed perception algorithm can achieve better sparse recovery than the matched filter imaging algorithm, but there is a large dimension of the measurement matrix and high computational complexity. For the problems of difficult data processing and large dimensions of measurement matrix, a sparse imaging regularization model is constructed based on approximate observation, and an improved soft threshold iterative algorithm is used with adaptive step size, which improves the convergence performance, reduces the computational complexity of the sparse recovery dramatically and achieves a better quality of sparse imaging than the traditional compressed perception algorithm.

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Self-Dual Hadamard Bent Sequences

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Journal of Systems Science & Complexity 2023年第2期36卷 894-908页

作者： SHI Minjia LI Yaya CHENG Wei CRNKOVIC Dean KROTOV Denis SOLéPatrick Key Laboratory of Intelligent Computing Signal Processing Ministry of EducationSchool of Mathematical SciencesAnhui UniversityHefei 230601China State Key Laboratory of Information Security(Institute of Information Engineering) Chinese Academy of SciencesBeijing 100093China. LTCI Télécom ParisParis91120 PalaiseauFrance Secure-IC S.A.S. 104 Bd du Montparnasse75014 Paris Faculty of Mathematics University of RijekaNovosibirsk 630090Russia Sobolev Institute of Mathematics Novosibirsk 630090Russia Aix Marseille Univ CNRSCentrale MarseilleI2MMarseilleFrance

A new notion of bent sequence related to Hadamard matrices was introduced recently,motivated by a security application(Solé,et al.,2021).The authors study the self-dual class in length at most *** authors use three competing methods of generation:Exhaustion,Linear Algebra and Gr?bner *** Hadamard matrices and Bush-type Hadamard matrices provide many *** authors conjecture that if v is an even perfect square,a self-dual bent sequence of length v always *** authors introduce the strong automorphism group of Hadamard matrices,which acts on their associated self-dual bent *** authors give an efficient algorithm to compute that group.

关键词： Bent sequences bush-type Hadamard matrices Hadanard matrices PUF functions regular Hadamard matrices

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A Dual-band Low-profile Quadrifilar-Helix Antenna for Satellite Navigation System

A Dual-band Low-profile Quadrifilar-Helix Antenna for Satell...

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IEEE International Workshop on Electromagnetics, Applications and Student Innovation (iWEM)

作者： Jiahong Wang Junwei Qi Yingsong Li 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

A new dual-band low-profile quadrifilar-helical antenna (QHA) was presented. The spiral radiation arm of QHA is printed to three circular dielectric plates to reduce the antenna height. In this case, the radiation arm of the lower layer is connected to the feed, and the L-shaped branch is connected to the ground through a 50 ohm resistance. The radiation arm in the middle layer adds branches to realize dual frequency. The upper radiation arm rotates inward and folds, further realizing miniaturization. As a result, the height of QHA is only 20mm. Through CST simulation and optimization, The operating frequency bands of QHA are 1GHz - 1.45GHz and 1.54GHz - 1.74GHz. The beam width of QHA is more than 120°, which is to provide service for satellite navigating systems. The AR for the operation bands are less than 3dB.

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A RIS-Aided MIMO Secure Communication Scheme Based on Subarray Partition

A RIS-Aided MIMO Secure Communication Scheme Based on Subarr...

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International Conference on Computer and Communications (ICCC)

作者： Suzhen Wang Hui Zhi Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Anhui University Hefei China School of Electronic and Information Engineering Anhui University Hefei China

Subarray partition of reconfigurable intelligent surface (RIS) can significantly reduce the computational complexity of solving optimal reflection coefficients. However, there is no research about the RIS subarray partition of RIS-aided multiple-input multiple-output (MIMO) communication for the eavesdropper scenario. In this paper, we intend to solve the optimization subarray partition problem for the eavesdropper scenario, design a RIS-aided MIMO secure communication scheme based on subarray partition (RSC-SP). We consider minimizing the number of subarrays while satisfying secrecy rate requirements. First, this problem is described as a nonconvex combinatorial optimization problem, then we solve it by combining alternating optimization and bisection. In this scheme, we derive the closed expressions of the optimal transmit covariance matrix and the optimal reflection coefficients of RIS. The alternating optimization algorithm is used to jointly optimize the transmit covariance matrix and the reflection coefficients of RIS, the bisection method is used to calculate the minimum number of subarrays. Simulation results show that compared with the traditional scheme without subarray partition, RSC-SP can significantly reduce the computational complexity while meeting secrecy rate requirements.

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Talents Training in Antenna Engineering 5

Talents Training in Antenna Engineering

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

作者： Li, Yingsong Huang, Zhixiang Jiang, Tao Li, Yibing Ye, Fang Chung, Kwok L. College of Information and Communication Engineering Harbin Engineering University Harbin15001 China Anhui University Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education China School of Computer Science and Engineering Huizhou University Huizhou516007 China

ISBN: (数字)9781665472111

ISBN: (纸本)9781665472111

We propose the antenna developments from nature to engineering, which is a natural method to train student for designing antenna. Also, the interest of the students can be stimulated. Using this method, the students can get how to design antennas and will be interested on the antenna engineering. Then, young talents can be brought up. By using this strategy, a nature Logo is introduced and cooperated with the proposed talent training method to get new antennas. Also, the results for the developed antenna is also simulated and analyzed based on the theory from the text book. In the future, the proposed talents training techniques or method can also be expanded to other different research directions. © 2022 IEEE.

关键词： Antennas

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SSFam: Scribble Supervised Salient Object Detection Family

arXiv

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arXiv 2024年

作者： Liu, Zhengyi Deng, Sheng Wang, Xinrui Wang, Linbo Fang, Xianyong Tang, Bin Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei China School of Artificial Intelligence and Big Data Hefei University Hefei China

Scribble supervised salient object detection (SSSOD) constructs segmentation ability of attractive objects from surroundings under the supervision of sparse scribble lab.ls. For the better segmentation, depth and thermal infrared modalities serve as the supplement to RGB images in the complex scenes. Existing methods specifically design various feature extraction and multi-modal fusion strategies for RGB, RGB-Depth, RGB-Thermal, and Visual-Depth-Thermal image input respectively, leading to similar model flood. As the recently proposed Segment Anything Model (SAM) possesses extraordinary segmentation and prompt interactive capability, we propose an SSSOD family based on SAM, named SSFam, for the combination input with different modalities. Firstly, different modal-aware modulators are designed to attain modal-specific knowledge which cooperates with modal-agnostic information extracted from the frozen SAM encoder for the better feature ensemble. Secondly, a siamese decoder is tailored to bridge the gap between the training with scribble prompt and the testing with no prompt for the stronger decoding ability. Our model demonstrates the remarkable performance among combinations of different modalities and refreshes the highest level of scribble supervised methods and comes close to the ones of fully supervised methods. https://***/liuzywen/SSFam Copyright © 2024, The Authors. All rights reserved.

关键词： Image segmentation

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