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Progress in Electromagnetics Research Symposium - Fall (PIERS - FALL)

作者： Yan Xue Jie Wu Lihua Wang Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei China

ISBN: (数字)9781728153049

ISBN: (纸本)9781728153056

This paper presents a 1 × 4 circularly polarized patch antenna array with frequency agility. A compact 4-cell array patch antenna with low-profile (i.e., about 0.013λ 0 ) has been designed for circular polarization mono-pulse applications. By properly switching between the different states of these p-i-n diodes, four discrete operating frequency bands can be achieved. Circularly polarization can be achieved by the perturbation segment. A Rat-Race coupler based feed network is developed showing the high isolation between input terminals as well as efficient placement of sum and difference ports, including to generate sum and difference patterns for mono-pulse applications operating. Because of a suitable replacement of the sum and difference ports, the antenna radiation patterns were symmetrical. The simulated peak gains of the four discrete operating frequencies for 4.4 GHz, 4.7 GHz, 5.3 GHz and 5.6 GHz are 11.7 dBi, 12.0 dBi, 12.1 dBi, and 12.3 dBi, respectively. Both the null-depth at four different frequencies are less than -15 dBi. The simulation results show that the 3 dB axial ratio at four different center frequencies are 0.89 dB, 1.87 dB, 0.91 dB and 2.15 dB, respectively.

关键词： Antenna arrays Switches Patch antennas Pins Polarization Antenna radiation patterns

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Self-grouping convolutional neural networks

arXiv

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arXiv 2020年

作者： Guo, Qingbei Wu, Xiao-Jun Kittler, Josef Feng, Zhiquan Jiangsu Provincial Engineering Laboratory of Pattern Recognition and Computational Intelligence Jiangnan University Wuxi214122 China Shandong Provincial Key Laboratory of Network based Intelligent Computing University of Jinan Jinan250022 China Centre for Vision Speech and Signal Processing University of Surrey GuildfordGU2 7XH United Kingdom

Although group convolution operators are increasingly used in deep convolutional neural networks to improve the computational efficiency and to reduce the number of parameters, most existing methods construct their group convolution architectures by a predefined partitioning of the filters of each convolutional layer into multiple regular filter groups with an equal spatial group size and data-independence, which prevents a full exploitation of their potential. To tackle this issue, we propose a novel method of designing self-grouping convolutional neural networks, called SG-CNN, in which the filters of each convolutional layer group themselves based on the similarity of their importance vectors. Concretely, for each filter, we first evaluate the importance value of their input channels to identify the importance vectors, and then group these vectors by clustering. Using the resulting data-dependent centroids, we prune the less important connections, which implicitly minimizes the accuracy loss of the pruning, thus yielding a set of diverse group convolution filters. Subsequently, we develop two fine-tuning schemes, i.e. (1) both local and global fine-tuning and (2) global only fine-tuning, which experimentally deliver comparable results, to recover the recognition capacity of the pruned network. Comprehensive experiments carried out on the CIFAR-10/100 and ImageNet datasets demonstrate that our self-grouping convolution method adapts to various state-of-the-art CNN architectures, (Figure presented) Figure 1: Evolution of group convolutions. (a) Regular convolution. (b) Regular group convolution. (c) Permuting group convolution. (d) Learned group convolution. (d) Self-grouping convolution. Note that white channels represent the ignored input channels, and gray channels indicate the reused input channels. such as ResNet and DenseNet, and delivers superior performance in terms of compression ratio, speedup and recognition accuracy. We demonstrate the ability of SG-CNN

关键词： Convolution

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Analysis of Asymptotically Tight Approximation SER for Cooperative NOMA Systems

Analysis of Asymptotically Tight Approximation SER for Coope...

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International Conference on Communication Technology (ICCT)

作者： Dingcheng Zhu Yijing Yao Lei Xu Hongwei Zhang Hongyu Fang Xiaohui Li Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Anhui University Hefei china

The closed-form formula derivation of the power domain cooperative Non-Orthogonal Multiple Access (NOMA) system is of great significance for further improving the performance of the system. However, the system performance formulas of the channel capacity and the paired bit error rate Pairwise Error Probability (PEP) are too complicated, which have increased the difficulty in system performance optimization. Therefore, based on the Amplify Forward (AF) relay cooperative NOMA model, the signal Interference Noise Ratio (SINR) formulas of the two weak-user nodes are constructed. Through the assumption of that, the Symbol Error Rate (SER) of each user is fair, the simplification condition of Moment Generating Function (MGF) with the harmonic mean form is satisfied. Combined with the SER calculation formula of MGF, the system SER asymptotically tight approximation formula with simple structure is derived at high signal-to-noise ratio (SNR). The Monte Carlo simulation results show that, the formula can accurately describe the SER performance of the power domain cooperative NOMA system with the non-ideal Successive Interference Cancellation (SIC) system when SNR is high. Under the condition of certain total power, the optimal power distribution factor is solved in order to minimize the total system SER.

关键词： Conferences Communications technology

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Dynamic Multi-user Detection Scheme Based on CVA-SSAOMP Algorithm in Uplink Grant-Free NOMA

Dynamic Multi-user Detection Scheme Based on CVA-SSAOMP Algo...

引用

International Conference on Communication Technology (ICCT)

作者： Jian Zhang Shichao Bai Lei Xu Hongwei Zhang Hongyu Fang Xiaohui Li Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Anhui University Hefei China

In the uplink grant-free non-orthogonal multiple access (NOMA) scenario, since the active user at the sender has a structured sparsity transmission characteristic, the compressive sensing recovery algorithm is initially applied to the joint detection of the active user and the transmitted data. However, the existing compressive sensing recovery algorithms with unknown sparsity often require noise power or signal-to-noise ratio (SNR) as the priori conditions, which greatly reduces the algorithm adaptability in multi-user detection. Therefore, an algorithm based on cross validation aided structured sparsity adaptive orthogonal matching pursuit (CVA-SSAOMP) is proposed to realize multi-user detection in dynamic change communication scenario of channel state information (CSI). The proposed algorithm transforms the structured sparsity model into a block sparse model, and without the priori conditions above, the cross validation method in the field of statistics and machine learning is used to adaptively estimate the sparsity of active user through the residual update of cross validation. The simulation results show that, compared with the traditional orthogonal matching pursuit (OMP) algorithm, subspace pursuit (SP) algorithm and cross validation aided block sparsity adaptive subspace pursuit (CVA-BSASP) algorithm, the proposed algorithm can effectively improve the accurate estimation of the sparsity of active user and the performance of system bit error ratio (BER), and has the advantage of low-complexity.

关键词： Matching pursuit algorithms Heuristic algorithms signal processing algorithms Multiuser detection Machine learning algorithms Adaptation models Periodic structures

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Corona discharge-driven platform for precise manipulation of high-viscosity dielectric droplets on copper wires

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Sensors and Actuators B: Chemical 2025年 442卷

作者： Tang, Qiang Liu, Manfei Tan, Dengqin Wang, Yan Wang, Ziyi Cui, Xiaxia Zhang, Jia-Han Wang, Chengjun Xue, Changguo State Key Laboratory of Digital Intelligent Technology for Unmanned Coal Mining Anhui University of Science & Technology Huainan232001 China School of Artificial Intelligence Anhui University of Science and Technology Hefei231131 China Electronic-Photonic Smart Sensing Device R&D Team Inner Mongolia Key Laboratory of Intelligent Communication and Sensing and Signal Processing School of Electronic Information Engineering Inner Mongolia University Hohhot010021 China School of Artificial Intelligence Anhui Polytechnic University Wuhu241000 China School of Materials Science and Engineering Anhui University of Science and Technology Anhui Huainan232000 China

Dielectric fluids, including polymers, oils, and organic solvents, are integral to applications such as microreactors, optical devices, and thermal management systems due to their stability and resistance to evaporation. However, precise manipulation of dielectric droplets, especially those with high viscosity, remains challenging due to low surface tension and small contact angles. This study introduces a novel corona discharge-driven platform designed for the precise formation, transport, and control of dielectric droplets on one-dimensional copper wires. Utilizing dual needle-tip electrodes, the system generates localized electric fields that facilitate non-contact charge deposition, enabling reliable manipulation of droplets with viscosities up to 30,000 cSt. Comprehensive experiments demonstrate synchronized droplet movement with electrode motion, effective handling of complex geometries, and advanced operations such as droplet merging and splitting. Moreover, dielectric droplets are utilized as micro-containers for performing on-droplet chemical and biological assays. The platform also enables efficient aspiration and release of high-viscosity dielectric fluids, surpassing the capabilities of conventional pipette-based methods. These results highlight the platform's robustness, versatility, and strong potential for integration into next-generation microfluidic and lab-on-a-chip systems. © 2025 Elsevier B.V.

关键词： Bioassay

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Cancelable Finger Vein Template Based on Variable Curvature Gabor Gilter and Improved Canonical Correlation Analysis

Cancelable Finger Vein Template Based on Variable Curvature ...

引用

IEEE International Conference on Information Communication and signal processing (ICICSP)

作者： Lulu Ye Huabin Wang Yufeng Shi Liang Tao Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Anhui University Hefei China

At present, the biometric template algorithms with state of the art recognition performance cannot guarantee the security of the system, whereas the security biometric template algorithms usually suffer from inaccurate recognition. In order to improve both the recognition performance and security of feature template for finger vein, a cancelable template algorithm is proposed in this paper. Firstly, a variable curvature Gabor filter is designed for finger vein orientation feature extraction. The maximum and sub-maximum orientation of Gabor filter are combined with differential excitation respectively to generate joint distribution features, which serve as feature vectors of finger vein. Secondly, the extracted feature vectors are reduced dimension by PCA, and the reduced feature vectors are combined with the pseudo random matrix, which is produced by a token to generate a cancelable template to guarantee the security. Finally, cancelable templates in two orientations are fused to increase the irreversibility of templates by using the improved canonical correlation analysis. Extensive experiments on the SDUMLA-FV and PolyU databases demonstrate the superiority of the proposed method in terms of verification performance, diversity, revocability/reusability and irreversibility.

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A Compact Bandpass Filter Using Novel Microstrip Dual-mode Resonator with Hexagonal Structure

A Compact Bandpass Filter Using Novel Microstrip Dual-mode R...

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Progress in Electromagnetics Research Symposium - Fall (PIERS - FALL)

作者： Xin-Yu Ning Han-Ran Zhu Zhi-Xiang Huang Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei China

ISBN: (数字)9781728153049

ISBN: (纸本)9781728153056

A dual-mode bandpass filter with miniaturized size is presented in this paper. A hexagonal microstrip dual-mode resonator is employed to reduce the size of the filter. A pair of tortuous parallel coupled input and output structures are used to introduce the transmission zeros, which can improve the selectivity and the stopband of the filter. Compared to other dual-mode resonator filters, a compact advantage is also achieved with the presented design. A sample circuit is fabricated with the thin film technology to validate the design. The size of the filter is 4.98 × 4.57mm 2 , which is equivalent to $0.147 \times 0.134\lambda _g^2$ at 8.75GHz. The prototype filter has a fractional bandwidth of 5.7%, a low passband insertion loss of 0.6dB. Moreover, excellent out-of-band rejection characteristics are achieved in the hexagonal dual mode filter. Four transmission zeros are generated in the stopband to improve out-of-band rejection, and out of-band rejection greater than 20dB can be achieved in the stopband below 15GHz. In addition, a size reduction of approximately 30% is observed when compared with miniaturized rectangular ring patch resonators, for the same center frequency.

关键词： Microstrip resonators Resonant frequency Optical ring resonators Filtering theory Passband Perturbation methods

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A Low-Complexity and High-Efficient Pilot Allocation Scheme Based on User Grouping in Massive MIMO System

A Low-Complexity and High-Efficient Pilot Allocation Scheme ...

引用

International Conference on Communication Technology (ICCT)

作者： Xinying Zhao Yijing Yao Lei Xu Hongyu Fang Hongwei Zhang Xiaohui Li Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Anhui University Hefei China

Pilot allocation is one of the effective means to reduce pilot pollution in massive Multiple-Input Multiple-Output (MIMO) systems. The goal of this paper is to improve the uplink achievable sum rates of strong users, and ensure the quality of service (QoS) requirements of weak users at the same time, so that the sum rates of system can be improved. Combining with the technical advantage of pilot grouping, a low complexity pilot allocation scheme based on matching algorithm is proposed, which divides the users in the target cell into weak user group and strong user group, and adopts the minimum-maximum matching method to allocate pilots in weak user group. Through the introduction of Hungarian algorithm, a pilot allocation method is designed to ensure the fairness of the strong users. The simulation results show that, compared with the smart pilot allocation scheme, the pilot allocation scheme based on Hungarian algorithm, the pilot allocation scheme based on user grouping and the random pilot allocation scheme, the system performance of the proposed scheme has been effectively improved.

关键词： Resource management Pollution Uplink Interference Fading channels Antennas Massive MIMO

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Active Lighting Recurrence by Parallel Lighting Analogy for Fine-Grained Change Detection

arXiv

引用

arXiv 2020年

作者： Zhang, Qian Feng, Wei Wan, Liang Tian, Fei-Peng Wang, Xiaowei Tan, Ping School of Computer Science and Technology College of Intelligence and Computing Tianjin University TianJin300350 China State Administration of Cultural Heritage China School of Computer Software College of Intelligence and Computing Tianjin University TianJin300350 China Tianjin Key Lab for Advanced Signal Processing Civil Aviation University of China Dunhuang Research Academy Dunhuang Gansu China School of Computing Science Simon Fraser University Canada

—This paper studies a new problem, namely active lighting recurrence (ALR) that physically relocalizes a light source to reproduce the lighting condition from single reference image for a same scene, which may suffer from fine-grained changes during twice observations. ALR is of great importance for fine-grained visual inspection and change detection, because some phenomena or minute changes can only be clearly observed under particular lighting conditions. Therefore, effective ALR should be able to online navigate a light source toward the target pose, which is challenging due to the complexity and diversity of real-world lighting and imaging processes. To this end, we propose to use the simple parallel lighting as an analogy model and based on Lambertian law to compose an instant navigation ball for this purpose. We theoretically prove the feasibility, i.e., equivalence and convergence, of this ALR approach for realistic near point light source and small near surface light source. Besides, we also theoretically prove the invariance of our ALR approach to the ambiguity of normal and lighting decomposition. The effectiveness and superiority of the proposed approach have been verified by both extensive quantitative experiments and challenging real-world tasks on fine-grained change detection of cultural heritages. We also validate the generality of our approach to non-Lambertian scenes. Copyright © 2020, The Authors. All rights reserved.

关键词： Light sources

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Novel deep hybrid model for electricity price prediction based on dual decomposition

引用

Applied Energy 2025年 395卷

作者： Ghimire, Sujan Nguyen-Huy, Thong Deo, Ravinesh C. Casillas-Pérez, David Masrur Ahmed, A.A. Salcedo-Sanz, Sancho Artificial Intelligence Applications Laboratory School of Mathematics Physics and Computing University of Southern Queensland SpringfieldQLD4300 Australia Centre for Applied Climate Sciences University of Southern Queensland ToowoombaQLD4350 Australia Faculty of Information Technology Thanh Do University Kim Chung Hoai Duc Ha Noi100000 Viet Nam Department of Signal Processing and Communications Universidad Rey Juan Carlos Madrid Fuenlabrada28942 Spain Science Economics and Insights Division Department of Climate Change Energy the Environment and Water NSW Government SydneyNSW2141 Australia Department of Signal Processing and Communications Universidad de Alcalá Alcalá de Henares Madrid 28805 Spain

Electricity price (EP) forecasting is vital for effective market operation, strategic planning, and risk management in deregulated energy systems. However, the inherent volatility and complexity of electricity prices, shaped by demand supply dynamics, weather variability, and regulatory interventions, pose substantial challenges to accurate prediction. This study introduces a novel hybrid framework designed to improve forecasting accuracy by leveraging both signal decomposition and deep learning techniques. Specifically, the method integrates Variational Mode Decomposition (VMD) and Empirical Wavelet Transform (EWT) for noise reduction and feature extraction, followed by a Multi Resolution Convolution (MRC) layer and a Bidirectional Long Short Term Memory (BiLSTM) network to capture multiscale temporal patterns in electricity price data. The model is applied to half hourly electricity price data from South Australia spanning January 2018 to December 2022. Its performance is benchmarked against a suite of traditional and hybrid models using a comprehensive set of twelve evaluation metrics. The results reveal that the proposed hybrid model consistently outperforms all baselines across seasons and forecast horizons. Notably, during the spring period, it achieved a Normalized Root Mean Square Error of ≈4.87%, a Mean Absolute Percentage Error of ≈12.09%, and a Global Performance Index of ≈3.22. These improvements demonstrate the model's ability to effectively handle the non-linear and nonstationary nature of EP. Overall, the findings underscore the potential of combining advanced decomposition methods with deep learning architectures to deliver more accurate and robust EP forecasts, thereby offering valuable support for decision making in complex and evolving energy markets. © 2025 The Author(s)

关键词： Risk perception

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