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International Applied Computational Electromagnetics Society Symposium (ACES)

作者： G. S. Cheng Huihui Li Z. X. Huang Ministry of Education Key Laboratory of Intelligent Computing and Signal Processing Anhui University Hefei China

ISBN: (数字)9780996007894

ISBN: (纸本)9781728146331

An efficient characteristic mode solver is proposed for the solution of characteristic modes (CMs) of large-scale finite periodic arrays. Firstly, the CMs of an isolated reference element are obtained using the standard characteristic mode solver. Then, by choosing the first several CMs of the isolated reference element with larger mode significance (MS) to construct the entire domain basis functions, the proposed method can dramatically reduce the matrix dimension of the resultant generalized eigenvalue problem governed by the entire array structure, thereby significantly reduce the computational time and memory requirement.

关键词： Finite element analysis Eigenvalues and eigenfunctions Memory management Microwave antenna arrays Phased arrays

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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...

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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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Electromagnetic Compatibitility Analysis with Ultra-Wideband Simultaneous Switching Noise Suppression for Antenna-in-Package

Electromagnetic Compatibitility Analysis with Ultra-Wideband...

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International Applied Computational Electromagnetics Society Symposium (ACES)

作者： Hao-Ran Zhu Yu-Fa Sun Xian-Liang Wu Ministry of Education Key Laboratory of Intelligent Computing and Signal Processing Anhui University Hefei China

ISBN: (数字)9780996007894

ISBN: (纸本)9781728146331

In this paper, a compact power distribution network (PDN) structure with ultra-wideband simultaneous switching noise (SSN) mitigation for antenna in package is presented. Only one spiral slot is etched on the square patch of the EBG pattern, which is constituted the presented PDN structure. The equivalent circuit model is developed to analyze the mechanism of the electromagnetic compatibility behavior that a high-impedance is provided for reducing the SSN coupling. An ultra-wideband SSN mitigation performance is obtained from 0.35 GHz to 20 GHz under the suppression level of -40 dB. Good agreements are observed between the simulated and measured results.

关键词： Periodic structures Metamaterials Spirals Switches Equivalent circuits Integrated circuit modeling Power systems

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A Compact Circularly Polarized Mono-pulse Antenna with Frequency Agility

A Compact Circularly Polarized Mono-pulse Antenna with Frequ...

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

Cancelable Finger Vein Template Based on Variable Curvature ...

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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 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 ...

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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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Meta auxiliary learning for facial action unit detection

arXiv

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arXiv 2021年

作者： Li, Yong Shan, Shiguang Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information Ministry of Education School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing210094 China Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences Institute of Computing Technology Cas Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China Cas Center for Excellence in Brain Science and Intelligence Technology

Despite the success of deep neural networks on facial action unit (AU) detection, better performance depends on a large number of training images with accurate AU annotations. However, labeling AU is time-consuming, expensive, and error-prone. Considering AU detection and facial expression recognition (FER) are two highly correlated tasks, and facial expression (FE) is relatively easy to annotate, we consider learning AU detection and FER in a multi-task manner. However, the performance of the AU detection task cannot be always enhanced due to the negative transfer in the multi-task scenario. To alleviate this issue, we propose a Meta Auxiliary Learning method (MAL) that automatically selects highly related FE samples by learning adaptative weights for the training FE samples in a meta learning manner. The learned sample weights alleviate the negative transfer from two aspects: 1) balance the loss of each task automatically, and 2) suppress the weights of FE samples that have large uncertainties. Experimental results on several popular AU datasets demonstrate MAL consistently improves the AU detection performance compared with the state-of-the-art multi-task and auxiliary learning methods. MAL automatically estimates adaptive weights for the auxiliary FE samples according to their semantic relevance with the primary AU detection task. Copyright © 2021, The Authors. All rights reserved.

关键词： Deep neural networks

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Graph jigsaw learning for cartoon face recognition

arXiv

引用

arXiv 2021年

作者： Li, Yong Lao, Lingjie Cui, Zhen Shan, Shiguang Yang, Jian Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information Ministry of Education School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing210094 China Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences Institute of Computing Technology CAS Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China CAS Center for Excellence in Brain Science and Intelligence Technology

Cartoon face recognition is challenging as they typically have smooth color regions and emphasized edges, the key to recognize cartoon faces is to precisely perceive their sparse and critical shape patterns. However, it is quite difficult to learn a shape-oriented representation for cartoon face recognition with convolutional neural networks (CNNs). To mitigate this issue, we propose the GraphJigsaw that constructs jigsaw puzzles at various stages in the classification network and solves the puzzles with the graph convolutional network (GCN) in a progressive manner. Solving the puzzles requires the model to spot the shape patterns of the cartoon faces as the texture information is quite limited. The key idea of GraphJigsaw is constructing a jigsaw puzzle by randomly shuffling the intermediate convolutional feature maps in the spatial dimension and exploiting the GCN to reason and recover the correct layout of the jigsaw fragments in a self-supervised manner. The proposed GraphJigsaw avoids training the classification model with the deconstructed images that would introduce noisy patterns and are harmful for the final classification. Specially, GraphJigsaw can be incorporated at various stages in a top-down manner within the classification model, which facilitates propagating the learned shape patterns gradually. GraphJigsaw does not rely on any extra manual annotation during the training process and incorporates no extra computation burden at inference time. Both quantitative and qualitative experimental results have verified the feasibility of our proposed GraphJigsaw, which consistently outperforms other face recognition or jigsaw-based methods on two popular cartoon face datasets with considerable improvements. © 2021, CC BY-NC-SA.

关键词： Face recognition

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