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19th IEEE International Conference on Communication Technology, ICCT 2019

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

ISBN: (纸本)9781728105352

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. © 2019 IEEE.

关键词： Bit error rate

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A Millimeter-Wave Wideband Integrated Log-Periodic Antenna Array

A Millimeter-Wave Wideband Integrated Log-Periodic Antenna A...

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Cross Strait Quad-Regional Radio Science and Wireless Technology Conference (CSQRWC)

作者： Daosheng Huang Guanghui Xu Jie Wu Hui Xu Li-Xia Yang Zhi-Xiang Huang Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei China

ISBN: (数字)9781728181813

ISBN: (纸本)9781728181820

The millimeter-Wave (mm-Wave) wideband integrated log-periodic antenna array based on multilayer PCB is proposed in this paper. The antenna array is simulated and designed to operate at the mm-Wave band of 32-47 GHz with the impedance bandwidth of 37.5%. Differential feeding is adopted to reduce the cross polarization, and EBG structure is used to improve the back lobe. The simulated maximum gain of the array is 11 dBi and the cross-polarization ratio is less than -40 dB. Due to its wide bandwidth, high gain and low cross polarization, the proposed array will be a suitable scheme for many mm-Wave applications.

关键词： Millimeter wave technology Nonhomogeneous media Broadband antennas Gain Wideband Antenna arrays Periodic structures

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A Novel FDTD Algorithm Based on the Vector and Scalar Potentials Equations 5

A Novel FDTD Algorithm Based on the Vector and Scalar Potent...

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5th IEEE International Conference on Computational Electromagnetics, ICCEM 2019

作者： Liu, Zhipeng Xie, Guoda Wu, Bo Ren, Xingang Fang, Ming Huang, Zhixiang Key Laboratory of Intelligent Computing Signal Processing Ministry of Education Anhui University Hefei China

ISBN: (纸本)9781538671115

As the advance in nanotechnology, the length of electronic devices down to nano-scale structure. It is important to consider multi-scale phenomena ruled by the Maxwell's equation in the finite-difference time-domain (FDTD) simulation. This paper provides an alternate approach for solving the vector and scalar potentials (A and Φ) formulation of Maxwell's equations instead of the fields (E and H) which might suffer from low frequency breakdown problem. This new approach is more suitable for multi-scale problem since it is stable in the long wavelength regime which established the proposed method as a better algorithm in the electromagnetic simulation. © 2019 IEEE.

关键词： Maxwell equations

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Energy Consumption and Time Delay optimization of MEC Based on MultiDimensional Game 5

Energy Consumption and Time Delay optimization of MEC Based ...

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5th IEEE International Conference on Cloud computing and Big Data Analytics, ICCCBDA 2020

作者： Wang, Hui Wang, Yi Lu, Xingjun Hu, Yanjun Anhui University Key Laboratory of Intelligent Computing Signal Processing Ministry of Education Hefei230601 China Key Laboratory of Wireless Sensor Network & Communication Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai200050 China

ISBN: (纸本)9781728160245

Mobile edge computing (MEC) reduces latency and power consumption of mobile devices by deploying servers on the network edge. Due to the limited computing resources of the MEC server, excessive offloading of the users in local cells will bring unexpected queuing delay and high energy consumption. To deal with these problems, this paper proposes a Multi-user Queue Offloading multi-dimensional game algorithm (MQO). By the algorithm, users could choose the most suitable strategy, in which the strategy space is two-dimensional to satisfy different needs of different users to a certain extent, including the offload strategy and power control of users. Simulation results show that MQO can improve the performance of both overhead and offloading number with the increase of users. © 2020 IEEE.

关键词： Energy utilization

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A Verlet Time-stepping Nodal DGTD Method for Electromagnetic Scattering and Radiation 5

A Verlet Time-stepping Nodal DGTD Method for Electromagnetic...

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5th IEEE International Conference on Computational Electromagnetics, ICCEM 2019

作者： Wang, Yulong Zhao, Ran Huang, Zhixiang Wu, Xianliang Key Laboratory of Intelligent Computing Signal Processing Ministry of Education Anhui University Hefei China

ISBN: (纸本)9781538671115

In this paper, a discontinuous Galerkin time domain (DGTD) method is proposed to solve electromagnetic radiation and scattering problems. In this method, for the electromagnetic radiation problem, the dipole source excitation is introduced by the Total field / Scattering field (TF/SF) boundary condition. On the basis of TF/SF boundary condition, an equivalent principle (EP) based boundary condition is also introduced. For the electromagnetic scattering problem, the plane wave excitation is introduced by pure scattered field method. For all the cases, uniaxial perfectly matched layer (UPML) is used as the truncated boundary condition to enhance the reflection wave absorption. At the same time, the method uses nodal local basis function (for spatial discretization) and Verlet method (for time integration) to solve Maxwell equation. Numerical results show the effectiveness and accuracy of the algorithm. © 2019 IEEE.

关键词： Boundary conditions

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Dynamic Multi-user Detection Scheme Based on CVA-SSAOMP Algorithm in Uplink Grant-Free NOMA 19

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

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19th IEEE International Conference on Communication Technology, ICCT 2019

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

ISBN: (纸本)9781728105352

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. © 2019 IEEE.

关键词： Multiuser detection

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High order SF-SFDTD method for solving the time-dependent Schrödinger equation

High order SF-SFDTD method for solving the time-dependent Sc...

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International Applied Computational Electromagnetics Society Symposium (ACES)

作者： Pan Pan Guoda Xie Zhixiang Huang Guilin Hou Ziheng Song School of Electronic and Information Engineering Anhui university Hefei China Education of Anhui Province. Anhui Province Key Laboratory of Target Recognition and Feature Extraction Luan Anhui China Ministry of Education. the Key Laboratory of Intelligent Computing and Signal Processing Hefei China Key Laboratory of Electromagnetic Environmental Sensing Anhui Province Anhui University Hefei China Anhui university Hefei China

A high-order spatial filtering-symplectic finite difference time domain (SF-SFDTD) scheme with controllable stability condition is proposed to solve the time-dependent Schrödinger equation (TDSE). Firstly, the higher-order symplectic framework for the discretization of Schrödinger equation is described, and then the spatial filtering method is carried out to extend the stability of the standard SFDTD method. Finally, a numerical example is given to evaluate the correctness of the SF-SFDTD method in numerical solving Schrödinger equation.

关键词： Filtering Filtering algorithms Computational electromagnetics Mathematical models Time-domain analysis Numerical stability Standards

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Unified-modal Salient Object Detection via Adaptive Prompt Learning

arXiv

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arXiv 2023年

作者： Wang, Kunpeng Li, Chenglong Tu, Zhengzheng Liu, Zhengyi Luo, Bin Information Materials and Intelligent Sensing Laboratory of Anhui Province Anhui Provincial Key Laboratory of Multimodal Cognitive Computation School of Computer Science and Technology Anhui University Hefei230601 China Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei China Anhui Provincial Key Laboratory of Multimodal Cognitive Computation School of Artificial Intelligence Anhui University Hefei230601 China The Institute of Physical Science and Information Technology Anhui University Hefei230601 China

Existing single-modal and multi-modal salient object detection (SOD) methods focus on designing specific architectures tailored for their respective tasks. However, developing completely different models for different tasks leads to labor and time consumption, as well as high computational and practical deployment costs. In this paper, we attempt to address both single-modal and multi-modal SOD in a unified framework called UniSOD, which fully exploits the overlapping prior knowledge between different tasks. Nevertheless, assigning appropriate strategies to modality variable inputs is challenging. To this end, UniSOD learns modality-aware prompts with task-specific hints through adaptive prompt learning, which are plugged into the proposed pre-trained baseline SOD model to handle corresponding tasks, while only requiring few learnable parameters compared to training the entire model. Each modality-aware prompt is generated from a switchable prompt generation block, which adaptively performs structural switching based on single-modal and multi-modal inputs without human intervention. Through end-to-end joint training, UniSOD achieves overall performance improvement on 14 benchmark datasets for RGB, RGB-D, and RGB-T SOD, which demonstrates that our method effectively and efficiently unifies single-modal and multi-modal SOD tasks. The code and results are available at https://***/Angknpng/UniSOD. Copyright © 2023, The Authors. All rights reserved.

关键词： Object detection

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Federated Client-tailored Adapter for Medical Image Segmentation

arXiv

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arXiv 2025年

作者： Hu, Guyue Song, Siyuan Kang, Yukun Yin, Zhu Zhao, Gangming Li, Chenglong Tang, Jin Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Anhui Provincial Key Laboratory of Security Artificial Intelligence School of Artificial Intelligence Anhui University Hefei230601 China School of Internet Anhui University Hefei230601 China Key Laboratory 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 Department of Computer Science The University of Hong Kong Hong Kong

Medical image segmentation in X-ray images is beneficial for computer-aided diagnosis and lesion localization. Existing methods mainly fall into a centralized learning paradigm, which is inapplicable in the practical medical scenario that only has access to distributed data islands. Federated Learning has the potential to offer a distributed solution but struggles with heavy training instability due to client-wise domain heterogeneity (including distribution diversity and class imbalance). In this paper, we propose a novel Federated Client-tailored Adapter (FCA) framework for medical image segmentation, which achieves stable and client-tailored adaptive segmentation without sharing sensitive local data. Specifically, the federated adapter stirs universal knowledge in off-the-shelf medical foundation models to stabilize the federated training process. In addition, we develop two client-tailored federated updating strategies that adaptively decompose the adapter into common and individual components, then globally and independently update the parameter groups associated with common client-invariant and individual client-specific units, respectively. They further stabilize the heterogeneous federated learning process and realize optimal client-tailored instead of sub-optimal global-compromised segmentation models. Extensive experiments on three large-scale datasets demonstrate the effectiveness and superiority of the proposed FCA framework for federated medical segmentation. © 2025, CC BY.

关键词： Federated learning

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14th International Conference on Bio-inspired computing: Theories and Applications, BIC-TA 2019

作者： Sun, Dengdi Sun, Haifeng Wu, Hang Liang, Huadong Ding, Zhuanlian Key Lab of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei230601 China iFlytek Co. Ltd. Hefei230088 China School of Internet Anhui University Hefei230039 China

ISBN: (纸本)9789811534140

Determining the functional roles of proteins is a vital task to understand life at molecular level and has great biomedical and pharmaceutical implications. With the development of novel high-throughput techniques, enormous amounts of protein-protein interaction (PPI) data are collected and provide an important and feasible way for studying protein function predictions. According to this, many approaches assign biological functions to all proteins using PPI networks directly. However, due to the extreme complexity of the topology structure of real PPI networks, it is very difficult and time consuming to seek the global optimization or clustering on the networks. In addition, biological functions are often highly correlated, which makes functions assigned to proteins are not independent. To address these challenges, in this paper we propose a two-stage function annotation method with robust feature selection. First, we transform the network into the low-dimensional representations of nodes via manifold learning. Then, we integrate the functional correlation into the framework of multi-label linear regression, and introduce robust sparse penalty to achieve the function assignment and representative feature selection simultaneously. For the optimization, we design an efficient algorithm to iteratively solve several subproblems with closed-form solutions. Extensive experiments against other baseline methods on Saccharomyces cerevisiae data demonstrate the effectiveness of the proposed approach. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Proteins

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