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第四届遥感与无线通信国际会议

作者： Jing Jin Rui Deng Tiansheng Liu Liping Li Key Laboratory of Intelligent Computing and Signal Processing (Ministry of Education) Anhui University Department of Electronic Engineering and Information Science University of Science and Technology

In additive white Gaussian noise（AWGN） channels, construction of polar codes is needed for every operating signal-to-noise ratio（SNR）. Recently, the proposal of the design-SNR reduces the computation effort in constructing polar codes. In this paper, we prove that although the BER performance of the design-SNR construction is not affected, the packet-error-rate（PER） performance is degraded compared with the point-by-point construction. Therefore, a concatenation scheme is proposed to improve the degraded PER performance. Results show the validity of the proposed concatenation scheme when employing the design-SNR construction.

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Simulating Maxwell-Schrodinger Equations by High-Order Symplectic FDTD Algorithm

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IEEE JOURNAL ON MULTISCALE AND MULTIPHYSICS COMPUTATIONAL TECHNIQUES 2019年 4卷 143-151页

作者： Xie, Guoda Huang, Zhixiang Fang, Ming Sha, Wei E., I Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei China Key Laboratory of Micro-Nano Electronic Devices and Smart Systems of Zhejiang Province College of Information Science and Electronic Engineering Zhejiang University Hangzhou China

A novel symplectic algorithm is proposed to solve the Maxwell Schrodinger (M-S) system for investigating light-matter interaction. Using the fourth-order symplectic integration and fourth-order collocated differences, M-S equations are discretized in temporal and spatial domains, respectively. The symplectic finite-difference time-domain (SFDTD) algorithm is developed for accurate and efficient study of coherent interaction between electromagnetic fields and artificial atoms. Particularly, the Dirichlet boundary condition is adopted for modeling the Rabi oscillation problems under the semiclassical framework. To implement the Dirichlet boundary condition, image theory is introduced, tailored to the high-order collocated differences. For validating the proposed SFDTD algorithm, three-dimensional numerical studies of the population inversion in the Rabi oscillation are presented. Numerical results show that the proposed high-order SFDTD(4, 4) algorithm exhibits better numerical performance than the conventional FDTD(2, 2) approach at the aspects of accuracy and efficiency for the long-term simulation. The proposed algorithm opens up a promising way toward a high-accurate energy-conservation modeling and simulation of complex dynamics in nanoscale light-matter interaction.

关键词： Maxwell Schrodinger (M-S) equations nanoscale light-matter interaction Rabi oscillation symplectic finite-difference time-domain (SFDTD)

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Designs in finite metric spaces: A probabilistic approach

arXiv

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arXiv 2021年

作者： Shi, Minjia Rioul, Olivier Solé, Patrick Key Laboratory of Intelligent Computing & Signal Processing of Ministry of Education School of Mathematical Sciences Anhui University Hefei230601 China Telecom ParisTech Palaiseau France I2M Aix-Marseille Univ. Centrale Marseille CNRS Marseille France

A finite metric space is called here distance degree regular if its distance degree sequence is the same for every vertex. A notion of designs in such spaces is introduced that generalizes that of designs in Q-polynomial distance-regular graphs. An approximation of their cumulative distribution function, based on the notion of Christoffel function in approximation theory is given. As an application we derive limit laws on the weight distributions of binary orthogonal arrays of strength going to infinity. An analogous result for combinatorial designs of strength going to infinity is *** Codes Primary 05E35, Secondary O5E20, 05E24 Copyright © 2021, The Authors. All rights reserved.

关键词： Orthogonal functions

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Multi-modal Remote Sensing Image Registration via Modality Perception and Self-Supervised Position Estimation

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IEEE Transactions on Geoscience and Remote Sensing 2025年 63卷

作者： Xiao, Yun Zhang, Chunlei Jiang, Bo Chen, Yuan Tang, Jin Anhui University Key Laboratory of Intelligent Computing & Signal Processing (Anhui University) Anhui Provincial Key Laboratory of Security Artificial Intelligence School of Artificial Intelligence Hefei 230601 China Anhui University Information Materials and Intelligent Sensing Laboratory of Anhui Province Anhui Provincial Key Laboratory of Multimodal Cognitive Computation School of Computer Science and Technology Hefei 230601 China Anhui University School of Internet Hefei 230601 China

Multi-modal remote sensing images registration ensures that images from different sensors or modalities are spatial and informational consistent for effective comparison and analysis. However, due to the non-linear modality gaps that exist between images, making it difficult to focus only on the spatial position differences of the images and ignore the modality gaps. In this paper, to address this issue, we propose a new framework for Multi-Modal remote sensing image Registration, named MMRNet. The proposed framework comprises the following main aspects. First, a novel self-supervised Positional Misalignment Estimator (PME) is designed for multi-modal image registration. PME is able to efficiently overcome the modality gaps and learn the positional differences between multi-modal images more reliably, optimizing the registration loss by minimizing the positional differences directly. Then, a new paradigm of modality translation, termed Modality Perception Module (MPM), is introduced to effectively learn modality gaps and perform modality translation in the case of positional misalignment. Finally, we further design the modality perception guidance loss to supervise the modality translation task, which can encourage the fidelity of the generated pseudo-modality images. Our registration network integrates both rigid registration model and non-rigid registration model. Experimental results demonstrate that the proposed registration framework can obtain obviously superior performance in both rigid and non-rigid image registration tasks on optical-SAR data, optical-map data and optical-infrared data. © 1980-2012 IEEE.

关键词： image registration modality translation Multi-modal learning remote sensing processing rigid and non-rigid transformation

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Challenge-aware U-net for breast lesion segmentation in ultrasound images

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Pattern Recognition 2025年 168卷

作者： Dengdi Sun Changxu Dong Yuchen Yan Bo Jiang Yayang Duan Zhengzheng Tu Chaoxue Zhang Key Laboratory of Intelligent Computing & Signal Processing (ICSP) Ministry of Education School of Artificial Intelligence Anhui University China Institute of Artificial Intelligence Hefei Comprehensive National Science Center China Anhui Provincial Key Laboratory of Multimodal Cognitive Computing School of Computer Science and Technology Anhui University China Department of Ultrasound the First Affiliated Hospital of Anhui Medical University China

Deep learning methods can enhance the efficiency of tumor segmentation in breast ultrasound (BUS) images. However, noise interference, small tumors, and blurred boundaries can reduce segmentation accuracy. We design a three-branch challenge-aware U-net (CAU-net) to address these main challenges in BUS images. Our CAU-net extracts the features from three challenge-aware encoders in parallel first. Secondly, we propose an adaptive aggregation layer (AAL) to merge the multi-scale features of three challenging branches, enabling the network to adaptively handle different breast lesion samples with these main challenges. To further enhance the accuracy of segmentation, we introduce the graph reasoning module (GRM) to the network to model the correlation between the channels of the features and acquire the global information in the features. The result of our experiment on two datasets demonstrates the superiority of CAU-net over the advanced medical image segmentation methods. Our code can be downloaded from https://***/tzz-ahu .

关键词： Image segmentation

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Zero sum sets in abelian groups

arXiv

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arXiv 2021年

作者： Shi, Minjia Krotov, Denis Li, Xiaoxiao Solé, Patrick Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Mathematics Sciences Anhui University HefeiAnhui China Sobolev Institute of Mathematics Novosibirsk630090 Russia I2M CNRS Centrale Marseille University of Aix-Marseille Marseilles France

The distribution of cardinalities of zero-sum sets in abelian groups is completely determined. A summation involving the Möbius function is given for the general abelian group, while in many special cases, including the case of elementary abelian groups, solved earlier by Li and Wan, it has a compact form. The proof involves two different Möbius transforms, on positive integers and on set *** Codes 05A18, 05E40, 68P27 Copyright © 2021, The Authors. All rights reserved.

关键词： Group theory

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Community-Grouping Based Particle Swarm optimisation Algorithm for Feature Selection

Community-Grouping Based Particle Swarm optimisation Algorit...

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Congress on Evolutionary Computation

作者： Jianfeng Qiu Jiangchuan Wan Lei Zhang Fan Cheng Yongkang Luo Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Anhui University China School of Computer Science and Technology Anhui University Hefei China

ISBN: (数字)9781728169293

ISBN: (纸本)9781728169309

As a frequently-used dimensionality reduction technique in machine learning, feature selection has attracted interests in the last decade. Since feature selection is essentially a combinatorial optimization problem, how to search the valuable feature subset is a challenging optimization task. Particle swarm optimization (PSO) algorithm and its variations have shown their competitiveness in solving feature selection problem. However, they have been proven to be easily trapped into the local optimal in high-dimensional space due to their intrinsic characteristic of quick convergence. To this end, an effective binary particle swarm optimization algorithm, named CBPSOFS, is proposed for feature selection, where a community-grouping based adaptive updating strategy is designed to avoid trapping into the local optimum and enhance the performance of PSO algorithm in feature selection. To be specific, the correlationship among features is used to construct the feature network, where multiple feature groups are obtained by dividing the achieved feature network. Considering that a community usually contains multiple similar features, the proposed adaptive updating strategy utilizes these feature groups to make the similar features not be included in the same particle so as to maintain the diversity of the population in the evolution. In addition, an information gain based initialization strategy and a history information based resetting strategy are also developed to improve the quality of obtained feature subset. Experimental results on several real world datasets have demonstrated the effectiveness of CBPSOFS in feature selection when compared with the several state-of-the-art baselines.

关键词： Feature extraction Sociology Statistics Particle swarm optimization Optimization History signal processing algorithms

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Butson Hadamard matrices, bent sequences, and spherical codes

arXiv

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arXiv 2023年

作者： Shi, Minjia Lu, Danni Armario, Andrés Egan, Ronan Ozbudak, Ferruh Solé, Patrick The Key Laboratory of Intelligent Computing Signal Processing Ministry of Education School of Mathematical Sciences Anhui University Hefei230601 China State Key Laboratory of Integrated Service Networks Xidian University Xi’an710071 China Departamento de Matemática Aplicada I Universidad de Sevilla Avda. Reina Mercedes s/n Seville41012 Spain School of Mathematical Sciences Dublin City University Ireland Faculty of Engineering and Natural Sciences Sabancı University Istanbul34956 Turkey I2M Aix Marseille Univ CNRS Centrale Marseille Marseilles France

We explore a notion of bent sequence attached to the data consisting of an Hadamard matrix of order n defined over the complex qth roots of unity, an eigenvalue of that matrix, and a Galois automorphism from the cyclotomic field of order q. In particular we construct self-dual bent sequences for various q ≤ 60 and lengths n ≤ 21. Computational construction methods comprise the resolution of polynomial systems by Groebner bases and eigenspace computations. Infinite families can be constructed from regular Hadamard matrices, Bush-type Hadamard matrices, and generalized Boolean bent functions. As an application, we estimate the covering radius of the code attached to that matrix over Zq. We derive a lower bound on that quantity for the Chinese Euclidean metric when bent sequences exist. We give the Euclidean distance spectrum, and bound above the covering radius of an attached spherical code, depending on its strength as a spherical design. © 2023, CC BY.

关键词： Spheres

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Development of Fast Periodic Characteristic Mode Analysis (PCMA) Tool

Development of Fast Periodic Characteristic Mode Analysis (P...

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IEEE International Conference on Computational Electromagnetics (ICCEM)

作者： G. S. Cheng Chao-Fu Wang Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Auhui University Hefei China Temasek Laboratories National University of Singapore Singapore Singapore

ISBN: (数字)9781728134482

ISBN: (纸本)9781728134499

This paper addresses how to develop theory of characteristic modes (TCM) for finite periodic arrays or structures with fully using their periodic property. For ease of reference, the developed method is called periodic characteristic mode analysis (PCMA) method. Its basic idea is that we adopt a small set of specially selected characteristic modes (CMs) of a reference cell (element) of the structure to build up entire-domain basis functions (EDBFs) defined on each cell of the array structure and apply them to represent the characteristic currents (CCs) of the whole structure. Making use of periodicity of the array can greatly reduce the matrix size of the resultant generalized eigenvalue equation and speed up its solution process.

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Iterated Problem Reformulation for Evolutionary Large-Scale Multiobjective Optimization

Iterated Problem Reformulation for Evolutionary Large-Scale ...

引用

Congress on Evolutionary Computation

作者： Cheng He Ran Cheng Ye Tian Xingyi Zhang Department of Computer Science and Engineering University Key Laboratory of Evolving Intelligent Systems of Guangdong Province Southern University of Science and Technology Shenzhen China Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Institutes of Physical Science and Information Technology Anhui University Hefei China Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei China

ISBN: (数字)9781728169293

ISBN: (纸本)9781728169309

Due to the curse of dimensionality, two main issues remain challenging for applying evolutionary algorithms (EAs) to large-scale multiobjective optimization. The first issue is how to improve the efficiency of EAs for reducing computation cost. The second one is how to improve the diversity maintenance of EAs to avoid local optima. Nevertheless, these two issues are somehow conflicting with each other, and thus it is crucial to strike a balance between them in practice. Thereby, we propose an iterated problem reformulation based EA for large-scale multiobjective optimization, where the problem reformulation based method and the decomposition based method are used iteratively to address the aforementioned issues. The proposed method is compared with several state-of-the-art EAs on a variety of large-scale multiobjective optimization problems. Experimental results demonstrate the effectiveness of our proposed iterated method in large-scale multiobjective optimization.

关键词： Sociology Convergence Pareto optimization Indexes Computer science

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