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2019 3rd International Conference on Data Mining, Communications and Information Technology (DMCIT 2019)

作者： Yin Wang Xiaohui Li Wenwu Wang Gongquan Zhang Hongwei Zhang Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Anhui University

In this paper,we propose a new user grouping and power allocation scheme based on beamforming for downlink non-orthogonal multiple access *** proposed user grouping scheme can effectively reduce the interference from the other user and other beams as well,and can effectively improve the weak user rate especially when the SNR is not *** addition,a power allocation scheme that can maximize the sum capacity while satisfying a certain fairness index is *** the simulation results,the user grouping and power allocation method proposed in this paper can not only improve the overall system throughput performance,but also improve the fairness of weak users.

关键词： SNR A New User Grouping and Power Allocation Scheme for Downlink Non-orthogonal Multiple Access Systems

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Multi-channel Compressed Sensing Optimization Based on Singular Value Decomposition

Multi-channel Compressed Sensing Optimization Based on Singu...

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2019第十一届数字图像处理国际会议

作者： Cheng Zhang Yuanyuan Zhu Jun Tang Qianwen Chen Meiqin Wang Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University

Distributed compressed sensing theory is applied to many practical problems,ECG signal,color imaging,*** order to improve the reconstruction accuracy of multi-dimensional signals,this paper applies singular value decomposition to the multi-measure vector problem in DCS,then distributed compressed sensing reconstruction method based on singular value decomposition is *** method can achieve row orthogonality of the measurement matrix and does not affect the design of the reconstruction *** experiments verify the effectiveness of the proposed method,which can significantly improve the reconstruction quality of the signal and the robustness to noise.

关键词： Distributed compressed sensing (DCS) Multiple measurement vector problem(MMV) singular value decomposition(SVD) Separable Design

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A Second-order C-bandpass Frequency Selective Surface

A Second-order C-bandpass Frequency Selective Surface

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International Conference on Microwave and Millimeter Wave Technology Proceedings

作者： Shenbing Wu Mingsheng Chen Meng Kong Liang Zhang Key Lab of Intelligent Computing & Signal Processing Ministry of Education Anhui University School of Electronic Engineering Huainan Normal University AnHui Province Key Laboratory of Simulation and Design for Electronic Information System Hefei Normal University

ISBN: (数字)9781728157337

ISBN: (纸本)9781728157344

A novel C-bandpass frequency selective surface(FSS) exhibiting miniaturized periodic parts is developed in this study. Such FSS acts as a bandpass filter at 4.03--7.87GHz. The proposed FSS exhibits miniaturization characteristics with the unit-cell dimension 0.12λ*0.12λ and the total thickness less than λ/28. Meantime, the simulation results reveal that the second-order FSS exhibits better stability under a variety of incident directions and polarization modes.

关键词： Frequency selective surfaces Microwave technology Surface waves Simulation Millimeter wave technology Stability analysis Periodic structures

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Multilevel Characteristic Basis Function Method with ACA for Accelerated Solution of Electrically Large Scattering Problems

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Transactions of Nanjing University of Aeronautics and Astronautics 2018年第3期35卷 449-454页

作者： Li Chenlu Sun Yufa Wang Zhonggen Wang Guohua Key Laboratory of Intelligent Computing & Signal Processing Ministry of EducationAnhui University College of Electrical and Information Engineering Anhui University of Science and Technology

The multilevel characteristic basis function method(MLCBFM)with the adaptive cross approximation(ACA)algorithm for accelerated solution of electrically large scattering problems is studied in this *** the conventional MLCBFM based on Foldy-Lax multiple scattering equations,the improvement is only made in the generation of characteristic basis functions(CBFs).However,it does not provide a change in impedance matrix filling and reducing matrix calculation procedure,which is *** reality,all the impedance and reduced matrix of each level of the MLCBFM have low-rank property and can be calculated ***,ACA is used for the efficient generation of two-level CBFs and the fast calculation of reduced matrix in this *** results are given to demonstrate the accuracy and efficiency of the method.

关键词： multilevel characteristic basis function method(MLCBFM) adaptive cross approximation(ACA) characteristic basis functions(CBFs) electromagnetic scattering

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Semantic knowledge transfer for semi-supervised medical image segmentation

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Engineering Applications of Artificial Intelligence 2025年 158卷

作者： Shiwei Zhou Haifeng Zhao Leilei Ma Dengdi Sun Key Laboratory of Intelligent Computing & Signal Processing (ICSP) Ministry of Education Anhui University Hefei 230601 China Anhui Provincial Key Laboratory of Multimodal Cognitive Computation Anhui University Hefei 230601 China School of Computer Science and Technology Anhui University Hefei 230601 China School of Artificial Intelligence Anhui University Hefei 230601 China Institute of Artificial Intelligence Hefei Comprehensive National Science Center Hefei 230026 China

In semi-supervised medical image segmentation, due to possible differences in information content and distribution between labeled and unlabeled data, dealing with the two separately usually prevents knowledge transfer from labeled to unlabeled data. This prevents the model from effectively sharing learned information between the two types of data. To alleviate this problem, we train labeled and unlabeled data as a whole. Semantic mixing of labeled and unlabeled data is achieved by selecting and exchanging some of the region images of both through a mask to generate complementary input views. In addition, due to the limited labeled data, the unlabeled data has a weak ability to distinguish categories in the feature space. Traditional methods rely on pixel positions to generate positive and negative samples for contrastive learning to solve this problem, but relying on pixel position sampling can easily lead to semantic inconsistency, which affects the effect of feature learning; therefore, to address this problem, we propose an innovative labeled data-guided inter-class contrastive learning strategy, which extracts the category features from labeled and unlabeled data and exploits the accurate category information in the labeled data to guide contrastive learning, while introducing a similarity-based ranking weighting mechanism. Combining the two designs, we propose a new semantic knowledge transfer framework for semi-supervised medical image segmentation. Experiments demonstrate a significant improvement in our model compared to State of the Art (SOTA) on the Automatic Cardiac Diagnosis Challenge (ACDC) dataset and the Left Atrium (LA) dataset.

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A Real-time LoRa-based IoT System for intelligent Meteorological Monitoring

A Real-time LoRa-based IoT System for Intelligent Meteorolog...

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International Conference on Computer and Communications (ICCC)

作者： Donghe Wang Hai Hu Haojun Yang Kan Zheng Ministry of Education Intelligent Computing and Communications (IC2) Lab Wireless Signal Processing and Networks (WSPN) Lab Key Laboratory of Universal Wireless Communications Beijing University of Posts and Telecommunications Beijing China

ISBN: (数字)9781728186351

ISBN: (纸本)9781728186368

Real-time monitoring of meteorological conditions has been arousing increasing attention in current production and life. However, considering the challenges of deployment costs and demand for low power consumption, existing monitoring system needs to be improved to meet the requirements of new Internet-of-Things (IoT) applications. Therefore, a wireless sensor network system dedicated for meteorological monitoring is studied based on Long Range (LoRa) in this paper. Firstly, our meteorological monitoring system is designed for real-time services such as agricultural production demand. Then, the implementation of the proposed system is presented in detail as well as the prototype system is deployed on the campus. Finally, various experiments are conducted to provide the results for demonstrating the reliability and effectiveness of the proposed system.

关键词： Wireless communication Wireless sensor networks Humidity measurement Production Real-time systems Internet of Things Monitoring

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Optimal Ternary Cubic Two-Weight Codes

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Chinese Journal of Electronics 2018年第4期27卷 734-738页

作者： SHI Minjia HUANG Daitao SOL Patrick Key Laboratory of Intelligent Computing & Signal Processing Ministry of EducationAnhui University School of Mathematical Sciences Anhui University CNRS/LAGA University of Paris 8

We study trace codes with defining set L,a subgroup of the multiplicative group of an extension of degree m of a certain ring of order 27. These codes are abelian, and their ternary images are quasi-cyclic of coindex three(a.k.a. cubic codes). Their Lee weight distributions are computed by using Gauss sums. These codes have three nonzero weights when m is singly-even. When m is odd, under some hypothesises on the size of L, we obtain two new infinite families of two-weight codes which are optimal. Applications of the image codes to secret sharing schemes are also given.

关键词： Three-weight codes Two-weight codes Gauss sums Trace codes

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Quantum circuits for the heat equation with physical boundary conditions via Schrödingerization

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Journal of Computational Physics 2025年 538卷

作者： Shi Jin Nana Liu Yue Yu School of Mathematical Sciences Institute of Natural Sciences MOE-LSC Shanghai Jiao Tong University Shanghai 200240 China University of Michigan-Shanghai Jiao Tong University Joint Institute Shanghai 200240 China School of Mathematics and Computational Science Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education National Center for Applied Mathematics in Hunan Hunan Key Laboratory for Computation and Simulation in Science and Engineering Xiangtan University Xiangtan 411105 Hunan China

This paper explores the explicit design of quantum circuits for quantum simulation of partial differential equations (PDEs) with physical boundary conditions. These equations and/or their discretized forms usually do not evolve via unitary dynamics, thus are not directly suitable for quantum simulation. Boundary conditions (either time-dependent or independent) make the problem more difficult. To tackle this challenge, the Schrödingerization method can be employed, which converts linear partial and ordinary differential equations with non-unitary dynamics into systems of Schrödinger-type equations, via the so-called warped phase transformation that maps the equation into one higher dimension. Despite advancements in Schrödingerization techniques, the explicit implementation of quantum circuits for solving general PDEs, especially with physical boundary conditions, remains underdeveloped. We present two methods for handling the inhomogeneous terms arising from time-dependent physical boundary conditions. One approach utilizes Duhamel’s principle to express the solution in integral form and employs linear combination of unitaries (LCU) for coherent state preparation. Another method applies an augmentation to transform the inhomogeneous problem into a homogeneous one. We then apply the quantum simulation technique from [1] to transform the resulting non-autonomous system to an autonomous system in one higher dimension. We provide detailed implementations of these two methods and conduct a comprehensive complexity analysis in terms of queries to the time evolution input oracle.

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Schrödingerization based quantum algorithms for the fractional Poisson equation

arXiv

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arXiv 2025年

作者： Jin, Shi Liu, Nana Yu, Yue School of Mathematical Sciences Institute of Natural Sciences MOE-LSC Shanghai Jiao Tong University Shanghai200240 China University of Michigan Shanghai Jiao Tong University Joint Institute Shanghai200240 China School of Mathematics and Computational Science Hunan Key Laboratory for Computation and Simulation in Science and Engineering Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education National Center for Applied Mathematics in Hunan Xiangtan University Hunan Xiangtan411105 China

We develop a quantum algorithm for solving high-dimensional fractional Poisson equations. By applying the Caffarelli-Silvestre extension, the d-dimensional fractional equation is reformulated as a local partial differential equation in d + 1 dimensions. We propose a quantum algorithm for the finite element discretization of this local problem, by capturing the steady-state of the corresponding differential equations using the Schrödingerization approach from [29, 39, 40]. The Schrödingerization technique transforms general linear partial and ordinary differential equations into Schrödinger-type systems, making them suitable for quantum simulation. This is achieved through the warped phase transformation, which maps the equation into a higher-dimensional space. We provide detailed implementations of the method and conduct a comprehensive complexity analysis, which can show up to exponential advantage – with respect to the inverse of the mesh size in high dimensions – compared to its classical counterpart. Specifically, while the classical method requires Oe(d1/233d/2h−d−2) operations, the quantum counterpart requires Oe(d33d/2h−2.5) queries to the block-encoding input models, with the quantum complexity being independent of the dimension d in terms of the inverse mesh size h−1. Numerical experiments are conducted to verify the validity of our formulation. © 2025, CC BY-NC-ND.

关键词： Poisson equation

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Full reconstruction of simplicial complexes from binary time-series data

Research Square

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Research Square 2021年

作者： Wang, Huan Ma, Chuang Chen, Han-Shuang Lai, Ying-Cheng Zhang, Hai-Feng The Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Mathematical Science Anhui University Hefei230601 China School of Internet Anhui University Hefei230601 China School of Physics and Material Science Anhui University Hefei230601 China School of Electrical Computer and Energy Engineering Arizona State University TempeAZ85287 United States

Previous efforts on data-based reconstruction focused on complex networks with pairwise or two-body interactions. There is a growing interest in networks with high-order or many-body interactions, raising the need to reconstruct such networks based on observational data. We develop a general framework combining statistical inference and expectation maximization to fully reconstruct 2-simplicial complexes with two- and three-body interactions based on binary time-series data from social contagion dynamics. We further articulate a two-step scheme to improve the reconstruction accuracy while significantly reducing the computational load. Through synthetic and real-world 2-simplicial complexes, we validate the framework by showing that all the connections can be faithfully identified and the full topology of the 2-simplicial complexes can be inferred. The effects of noisy data or stochastic disturbance are studied, demonstrating the robustness of the proposed framework. © 2021, CC BY.

关键词： Complex networks

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