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International Applied Computational Electromagnetics Society Symposium (ACES)

作者： Yuwen Wu Qiang Yang Kai Tang Jianhang Zou Jianming Zhuo Naixing Feng Yijun Cai Smart Sensing Integrated Circuit Engineering Research Center of Universities in Fujian Province Xiamen University of Technology Xiamen China Xiamen Wish Information Technology Co. Ltd Xiamen China Xiamen Blue Ocean Technology Co. Ltd Xiamen China Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei China

With regard to distance measurement in daily life, the traditional way is to measure the distance between objects through rulers. Nowadays, ultrasonic ranging, laser ranging, radar ranging, sonar ranging and other technologies have enriched the way of distance measurement. At the same time, it is possible to choose a suitable solution according to different actual environments. This paper design an intelligent ultrasonic ranging system through the research of ultrasonic characteristics and the application of existing ultrasonic ranging. The paper introduces the design ideas and process of the intelligent ultrasonic ranging system. Through the design of independent buttons, the normal mode ranging and the high-precision mode ranging are generated to achieve the division of the measurement range and accuracy. When the distance between the measured object and the intelligent ultrasonic ranging system is less than the preset value or exceeds the range of this mode, the buzzer will sound an alarm, so that the system can be used in more fields. The system detects the current ambient temperature in real time, so that the distance measurement can be compensated and modified by the temperature compensation algorithm in the system to achieve self-adaptation and reduce measurement errors.

关键词： Temperature measurement Performance evaluation Temperature distribution Laser radar Ultrasonic variables measurement Current measurement Measurement uncertainty

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Ekblom Promoting Adaptive Algorithm for System Identification

TechRxiv

引用

TechRxiv 2022年

作者： Huang, Xinqi Li, Yingsong Han, Xiao Tu, Huawei College of Information and Communication Engineering Harbin Engineering University Harbin150001 China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Anhui Hefei China College of Computer Science and Technology Harbin Engineering University Harbin150001 China Department of Computer Science and Information Technology La Trobe University MelbourneVIC3086 Australia

We propose an Ekblom promoting adaptive algorithm (EPAA) which uses Ekblom norm to construct a data reusing scheme to achieve better performance under impulsive noise (IN) environments. By exerting Ekblom-norm constraint on the a posterior error vector, a sliding window cost function is created to realize the EPAA that is derived to reduce IN effects. The derivation and theoretical convergence analysis of the EPAA are presented in detail. The simulation examples are setup to illustrate the superior performance of the EPAA compared to popular data reusing algorithms for system identification under IN environments. © 2022, CC BY.

关键词： Adaptive filtering

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Additive complementary dual codes over F4

arXiv

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arXiv 2022年

作者： Shi, Minjia Liu, Na Kim, Jon-Lark Solé, Patrick Key Laboratory of Intelligent Computing Signal Processing Ministry of Education School of Mathematical Sciences Anhui University Anhui Hefei230601 China School of Mathematical Sciences Anhui University Anhui Hefei230601 China Department of Mathematics Sogang University Seoul Korea Republic of Aix Marseille Univ CNRS Centrale Marseille I2M Marseille France

A linear code is linear complementary dual (LCD) if it meets its dual trivially. LCD codes have been a hot topic recently due to Boolean masking application in the security of embarked electronics (Carlet and Guilley, 2014). Additive codes over F4 are F4-codes that are stable by codeword addition but not necessarily by scalar multiplication. An additive code over F4 is additive complementary dual (ACD) if it meets its dual trivially. The aim of this research is to study such codes which meet their dual trivially. All the techniques and problems used to study LCD codes are potentially relevant to ACD codes. Interesting constructions of ACD codes from binary codes are given with respect to the trace Hermitian and trace Euclidean inner product. The former product is relevant to quantum *** Codes 94B05 © 2022, CC0.

关键词： Additives

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An Octagonal Iterative Fractal Antenna with Notch Band and UWB Characteristics

An Octagonal Iterative Fractal Antenna with Notch Band and U...

引用

Progress in Electromagnetic Research Symposium (PIERS)

作者： Yong Cai Shuping He Xingang Ren Zhixiang Huang Anhui Province Key Laboratory of Target Recognition and Feature Extraction Luan China Key Laboratory of Electromagnetic Environmental Sensing Anhui University Hefei China Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Institute of Physical Science and Information Technology Anhui University Hefei China

ISBN: (纸本)9781665409889

In this paper, based on the rectangular iterative technique, we propose an omnidirectional UWB fractal antenna by using microstrip line as feed. The antenna takes regular octagonal shape as patch element. Meanwhile, the iterative fractal and notch technique has been adopted to optimize the UWB antenna performance. After multiple iterations of the configured octagonal patch element, the optimized UWB performance can be obtained. The simulation results reveal that the operating bandwidth of the antenna meets Federal Communications Commission (FCC) broadband standard. Moreover, in order to avoid the electromagnetic interference in the X-band identified by the IEEE 521-2002 standard, we further adopt notch techniques and add the U-shaped gap to the microstrip line to achieve electromagnetic shielding. The impedance matching has been achieved for the antenna by imposing the slot on the ground. After optimizing the slot structure, the reflection of the antenna has reduced in the whole operating frequency band. The overall size of the ultra-wideband fractal antenna was designed to $25 \times 35 mm^{2}$ and was composed of FR-4 material with the relative dielectric constant $\varepsilon_{r} = 4.4$ and loss tangent angle $\tan \theta = 0.02$. After optimization, the antenna has good impedance matching and meets the UWB antenna omnidirectional standard. In 3.1–15.4GHz (excluding X-band), and the reflection coefficient S 11 is lower than -10 dB, voltage standing wave ratio (VSWR) is less than 2, maximum gain reaches 6dB. The results indicated that our proposed fractal antenna is promising for UWB antenna applications.

关键词： Slot antennas Impedance matching Voltage FCC Ultra wideband antennas Fractals Microstrip

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LLR processing of Polar Codes in Concatenation Systems

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China Communications 2019年第9期16卷 201-208页

作者： Ya Meng Yi Fang Chuan Zhang Liping Li Key Laboratory of Intelligent Computing and Signal Processing of the Ministry of Education of China Anhui UniversityHefei 230031China School of Information Engineering Guangdong University of TechnologyGuangzhou 510006China National Mobile Communications Research Laboratory Southeast UniversityNanjingChina

This paper studies the decoding performance of low-density parity-check(LDPC)codes in a serial concatenation system with polar codes employing the successive cancellation(SC)*** is known that the absolute incorrect log-likelihood ratio(LLR)values from the SC decoding can be very *** phenomenon dramatically deteriorates the error correcting performance of the outer LDPC *** this paper,the LLR values of polar codes are regulated by a log processing before being sent to the LDPC *** results show that the log processing is an efficient approach with a low optimization complexity compared with the existing procedures to improve the performance of the serial concatenation systems.

关键词： polar codes SC decoding LDPCcodes concatenation

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Co-training based prediction of multi-label protein–protein interactions

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Computers in Biology and Medicine 2024年 177卷 108623-108623页

作者： Tang, Tao Zhang, Xiaocai Li, Weizhuo Wang, Qing Liu, Yuansheng Cao, Xiaofeng School of Modern Posts Nanjing University of Posts and Telecommunications 9 Wenyuan Rd Jiangsu Nanjing210023 China 1 Fusionopolis Way Singapore138632 Singapore School of Management Nanjing University of Posts and Telecommunications 9 Wenyuan Rd Jiangsu Nanjing210023 China College of Computer Science and Electronic Engineering Hunan University 2 Lushan Rd Hunan Changsha410086 China Key Laboratory of Intelligent Computing & Signal Processing of Ministry of Education Anhui University 111 Jiulong Road Anhui Hefei230601 China School of Artificial Intelligence Jilin University 2699 Qianjin St Changchun Jilin130012 China

Prediction of protein–protein interaction (PPI) types enhances the comprehension of the underlying structural characteristics and functions of proteins, which gives rise to a multi-label classification problem. The nominal features describe the physicochemical characteristics of proteins directly, establishing a more robust correlation with the interaction types between proteins than ordered features. Motivated by this, we propose a multi-label PPI prediction model referred to as CoMPPI (Co-training based Multi-Label prediction of Protein–Protein Interaction). This approach aims to maximize the utility of both ordered and nominal features extracted from protein sequences. Specifically, CoMPPI incorporates graph convolutional network (GCN) and 1D convolution operation to process the complementary subsets of features individually, leveraging both local and contextualized information in a more efficient way. In addition, two multi-type PPI datasets were constructed to eliminate the duplication in previous datasets. We compare the performance of CoMPPI with three state-of-the-art methods on three datasets partitioned using distinct schemes (Breadth-first search, Depth-first search, and Random), CoMPPI consistently outperforms the other methods across all cases, demonstrating improvements ranging from 3.81% to 32.40% in Micro-F1. The subsequent ablation experiment confirms the efficacy of employing the co-training framework for multi-label PPI prediction, indicating promising avenues for future advancements in this domain. © 2024 Elsevier Ltd

关键词： Proteins

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LasHeR: A large-scale high-diversity benchmark for RGBT tracking

arXiv

引用

arXiv 2021年

作者： Li, Chenglong Xue, Wanlin Jia, Yaqing Qu, Zhichen Luo, Bin Tang, Jin Sun, Dengdi Information Materials and Intelligent Sensing Laboratory of Anhui Province Anhui Provincial Key Laboratory of Multimodal Cognitive Computation School of Artificial Intelligence Anhui University Hefei230601 China Information Materials and Intelligent Sensing Laboratory of Anhui Province 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

RGBT tracking receives a surge of interest in the computer vision community, but this research field lacks a large-scale and high-diversity benchmark dataset, which is essential for both the training of deep RGBT trackers and the comprehensive evaluation of RGBT tracking methods. To this end, we present a Large-scale High-diversity benchmark for short-term RGBT tracking (LasHeR) in this work. LasHeR consists of 1224 visible and thermal infrared video pairs with more than 730K frame pairs in total. Each frame pair is spatially aligned and manually annotated with a bounding box, making the dataset well and densely annotated. LasHeR is highly diverse capturing from a broad range of object categories, camera viewpoints, scene complexities and environmental factors across seasons, weathers, day and night. We conduct a comprehensive performance evaluation of 12 RGBT tracking algorithms on the LasHeR dataset and present detailed analysis. In addition, we release the unaligned version of LasHeR to attract the research interest for alignment-free RGBT tracking, which is a more practical task in real-world applications. The datasets and evaluation protocols are available at: https://***/mmic-lcl/Datasets-and-benchmark-code. Copyright © 2021, The Authors. All rights reserved.

关键词： Large dataset

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Exploring Invariance Matters for Domain Generalization

引用

IEEE Transactions on Image processing 2025年 34卷 3336-3351页

作者： Wang, Shanshan He, Houmeng Yang, Xun Liu, Zhipu Zhong, Yuanhong Zhang, Xingyi Wang, Meng Anhui University National Key Laboratory of Opto-Electronic Information Acquisition and Protection Technology Institutes of Physical Science and Information Technology Hefei230601 China University of Science and Technology of China School of Information Science and Technology Department of Electronic Engineering and Information Science Hefei230026 China Chongqing University of Technology School of Computer Science and Engineering Chongqing400054 China Chongqing University School of Microelectronics and Communication Engineering Chongqing400030 China Anhui University Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education School of Computer Science and Technology Hefei230601 China Hefei University of Technology School of Computer Science and Information Engineering Hefei230009 China

Domain generalization (DG) aims to solve the problem of significant performance degradation when target domain data collected from the Out-Of-Distribution (O.O.D). Previous efforts try to exploit invariant features in the source domain through CNN networks. However, inspired by causal mechanisms, we find that the complex spurious-invariant information is still hidden in this view invariant features, and the impact of domain and class discrepancies on extracting invariance has not been effectively mitigated. To alleviate these issues, we propose a self-weighted multi-view mining invariance domain generalization framework (SMIDG). On the one hand, to make up for the insufficiency of traditional single-view convolutional feature extraction networks, we propose to mine features from another frequency view and use the self-adaptive adversarial masks to eliminate some spurious correlations, ensuring causal invariance in the coarse-grained generalization. However, due to inconsistencies in discriminative information between interdomain and intra-domain samples, as well as inter-class and intra-class samples, the coarse-grained elimination of spurious associations does not fully resolve this issue. On the other hand, we also consider the fine-grained generalization from two aspects. Firstly, to better tackle the domain discrepancies, we propose a novel progressive contrastive learning strategy that learns the underlying specific features of samples while gradually mitigating domain discrepancies, thereby ensuring domain invariance in fine-grained generalization. Secondly, due to the issue of feature inconsistency, we adopt a self-adaptive hard sample mining method with information gain to ensure that the model pays more attention on hard disentangled samples, thus maintaining feature invariance. Extensive experiments on five benchmark datasets demonstrate that our method outperforms state-of-the-art approaches. © 1992-2012 IEEE.

关键词： Contrastive learning Feature extraction Frequency-domain analysis Training Data models Data mining Correlation Data augmentation Convolutional neural networks Computer science

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A New Energy-Efficient Flooding Broadcast Time Synchronization for Wireless Sensor Networks 6th

A New Energy-Efficient Flooding Broadcast Time Synchronizati...

引用

6th International Conference on Positive Systems, POSTA 2018

作者： Xia, Tengfei He, Shuping Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education School of Electrical Engineering and Automation Anhui University Hefei230601 China

ISBN: (纸本)9783030043261

With the increasing scale of wireless sensor networks (WSN), it inevitably exists some problems in time synchronization, such as the sensitivity to the data of the normal error range, the large energy consumption and the long synchronous convergence time. To solve these problems, a high precision energy efficient broadcast time synchronization algorithm is proposed in this paper. This algorithm firstly sets the membership degree of each class and each sample. Then, by constantly iterating and adjusting the membership degree until convergence, it gets the only cluster by calculating each data to improve the accuracy. Finally, the MATLAB simulation results show that the proposed algorithm can not only improve the time synchronization accuracy, but also reduce the overall energy consumption level of the whole WSN effectively. © 2019, Springer Nature Switzerland AG.

关键词： Wireless sensor networks

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Meta Network for Radar HRRP Noncooperative Target Recognition with Missing Aspects

Meta Network for Radar HRRP Noncooperative Target Recognitio...

引用

IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Long Tian Bo Chen Yang Peng Chuan Du Zhenhua Wu Hongwei Liu National Laboratory of Radar Signal Processing Xidian University Xi'an China School of Electronics and Communication Engeering Sun Yat-sen University Guangzhou China Key Laboratory of Intelligent Computing and Signal Processing Anhui University Hefei China

ISBN: (数字)9781728163741

ISBN: (纸本)9781728163758

We propose a meta network (MNet) for the problem of target-aspect missing in radar high-resolution range profile (HRRP)-based noncooperative target recognition, where a classifier must be generalized to new aspects not seen in the training set, given only a small number of HRRP data of each new aspect. The MNet is a time domain convolutional neural network (TCNN) that is built based upon recent progress in meta-learning. In effect, it learns a model that is easy and fast to fine-tune, allowing the adaptation to happen in the right space for fast learning. Besides, we construct a new controllable HRRP dataset suitable for the scenario of noncooperative target-aspect missing using electromagnetic simulation. Compared with the traditional methods, the MNet is more efficient and could achieve better performance. Extensive experiments on the simulated HRRP dataset are conducted to illustrate the effectiveness of the proposed method.

关键词： Task analysis Training Target recognition Radar Adaptation models Time-domain analysis Solid modeling

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