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NONMONOTONE LOCAL MINIMAX METHODS FOR FINDING MULTIPLE SADDLE POINTS

Journal of Computational mathematics 2024年第3期42卷 851-884页

作者： Wei Liu Ziqing Xie Wenfan Yi South China Research Center for Applied Mathematics and Interdisciplinary Studies South China Normal UniversityGuangzhou 510631China Key Laboratory of Computing and Stochastic Mathematics(Ministry of Education) Hunan Normal UniversityChangshaHunan 410081China Hunan Provincial Key Laboratory of Intelligent Information Processing and Applied Mathematics School of MathematicsHunan UniversityChangshaHunan 410082China

In this paper,by designing a normalized nonmonotone search strategy with the BarzilaiBorwein-type step-size,a novel local minimax method(LMM),which is a globally convergent iterative method,is proposed and analyzed to find multiple(unstable)saddle points of nonconvex functionals in Hilbert *** to traditional LMMs with monotone search strategies,this approach,which does not require strict decrease of the objective functional value at each iterative step,is observed to converge faster with less ***,based on a normalized iterative scheme coupled with a local peak selection that pulls the iterative point back onto the solution submanifold,by generalizing the Zhang-Hager(ZH)search strategy in the optimization theory to the LMM framework,a kind of normalized ZH-type nonmonotone step-size search strategy is introduced,and then a novel nonmonotone LMM is *** feasibility and global convergence results are rigorously carried out under the relaxation of the monotonicity for the functional at the iterative ***,in order to speed up the convergence of the nonmonotone LMM,a globally convergent Barzilai-Borwein-type LMM(GBBLMM)is presented by explicitly constructing the Barzilai-Borwein-type step-size as a trial step-size of the normalized ZH-type nonmonotone step-size search strategy in each ***,the GBBLMM algorithm is implemented to find multiple unstable solutions of two classes of semilinear elliptic boundary value problems with variational structures:one is the semilinear elliptic equations with the homogeneous Dirichlet boundary condition and another is the linear elliptic equations with semilinear Neumann boundary *** numerical results indicate that our approach is very effective and speeds up the LMMs significantly.

关键词： Multiple saddle points Local minimax method Barzilai-Borwein gradient method Normalized nonmonotone search strategy Global convergence

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An Efficient Multi-objective Approach Based on Golden Jackal Search for Dynamic Economic Emission Dispatch

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Journal of Bionic Engineering 2024年第3期21卷 1541-1566页

作者： keyu Zhong Fen Xiao Xieping Gao Key Laboratory of Computing and Stochastic Mathematics of Ministry of Education Hunan Normal UniversityChangsha410081China School of Mathematics and Statistics Hunan Normal UniversityChangsha410081China School of Computer Science Xiangtan UniversityXiangtan411105China Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing Hunan Normal UniversityChangsha410081China

Dynamic Economic Emission Dispatch(DEED)aims to optimize control over fuel cost and pollution emission,two conflicting objectives,by scheduling the output power of various units at specific *** many methods well-performed on the DEED problem,most of them fail to achieve expected results in practice due to a lack of effective trade-off mechanisms between the convergence and diversity of non-dominated optimal dispatching *** address this issue,a new multi-objective solver called Multi-Objective Golden Jackal Optimization(MOGJO)algorithm is proposed to cope with the DEED *** proposed algorithm first stores non-dominated optimal solutions found so far into an ***,it chooses the best dispatching solution from the archive as the leader through a selection mechanism designed based on elite selection strategy and Euclidean distance index *** mechanism can guide the algorithm to search for better dispatching solutions in the direction of reducing fuel costs and pollutant ***,the basic golden jackal optimization algorithm has the drawback of insufficient search,which hinders its ability to effectively discover more Pareto *** this end,a non-linear control parameter based on the cosine function is introduced to enhance global exploration of the dispatching space,thus improving the efficiency of finding the optimal dispatching *** proposed MOGJO is evaluated on the latest CEC benchmark test functions,and its superiority over the state-of-the-art multi-objective optimizers is highlighted by performance ***,empirical results on 5-unit,10-unit,IEEE 30-bus,and 30-unit systems show that the MOGJO can provide competitive compromise scheduling solutions compared to published DEED ***,in the analysis of the Pareto dominance relationship and the Euclidean distance index,the optimal dispatching solutions provided by MOGJO are the closest to the ideal solutions for minimizing fuel costs

关键词： Dynamic economic emission dispatch Multi-objective optimization Golden jackal Euclidean distance index

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APFA:Ameliorated Pathfinder Algorithm for Engineering Applications

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Journal of Bionic Engineering 2024年第3期21卷 1592-1616页

Pathfinder algorithm(PFA)is a swarm intelligent optimization algorithm inspired by the collective activity behavior of swarm animals,imitating the leader in the population to guide followers in finding the best food *** algorithm has the characteristics of a simple structure and high ***,PFA faces challenges such as insufficient population diversity and susceptibility to local optima due to its inability to effectively balance the exploration and exploitation *** paper proposes an Ameliorated Pathfinder Algorithm called APFA to solve complex engineering optimization ***,a guidance mechanism based on multiple elite individuals is presented to enhance the global search capability of the ***,to improve the exploration efficiency of the algorithm,the Logistic chaos mapping is introduced to help the algorithm find more high-quality potential solutions while avoiding the worst ***,a comprehensive following strategy is designed to avoid the algorithm falling into local optima and further improve the convergence *** three strategies achieve an effective balance between exploration and exploitation overall,thus improving the optimization performance of the *** performance evaluation,APFA is validated by the CEC2022 benchmark test set and five engineering optimization problems,and compared with the state-of-the-art metaheuristic *** numerical experimental results demonstrated the superiority of APFA.

关键词： Pathfinder algorithm Swarm intelligent Metaheuristic Engineering problems

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Security-Reliability Analysis and Optimization for Cognitive Two-Way Relay Network with Energy Harvesting

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China Communications 2024年第11期21卷 163-179页

作者： Luo Yi Zhou Lihua Dong Jian Sun Yang Xu Jiahui Xi Kaixin Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing Hunan Normal UniversityChangsha 410081China School of Electronic Information Central South UniversityChangsha 410075China

This paper investigates the security and reliability of information transmission within an underlay wiretap energy harvesting cognitive two-way relay *** the network,energy-constrained secondary network(SN)nodes harvest energy from radio frequency signals of a multi-antenna power *** SN sources exchange their messages via a SN decode-and-forward relay in the presence of a multiantenna eavesdropper by using a four-phase time division broadcast protocol,and the hardware impairments of SN nodes and eavesdropper are *** alleviate eavesdropping attacks,the artificial noise is applied by SN *** physical layer security performance of SN is analyzed and evaluated by the exact closed-form expressions of outage probability(OP),intercept probability(IP),and OP+IP over quasistatic Rayleigh fading ***,due to the complexity of OP+IP expression,a self-adaptive chaotic quantum particle swarm optimization-based resource allocation algorithm is proposed to jointly optimize energy harvesting ratio and power allocation factor,which can achieve security-reliability tradeoff for *** simulations demonstrate the correctness of theoretical analysis and the effectiveness of the proposed optimization algorithm.

关键词： artificial noise energy harvesting cognitive two-way relay network hardware impairments physical layer security security-reliability tradeoff self-adaptive quantum particle swarm optimization

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HRAM-VITON: High-Resolution Virtual Try-On with Attention Mechanism

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Computers, Materials & Continua 2025年第2期82卷 2753-2768页

作者： Yue Chen Xiaoman Liang Mugang Lin Fachao Zhang Huihuang Zhao College of Computer Science and Technology Hengyang Normal UniversityHengyang421002China Hunan Provincial Key Laboratory of Intelligent Information Processing and Application Hengyang421002China

The objective of image-based virtual try-on is to seamlessly integrate clothing onto a target image, generating a realistic representation of the character in the specified attire. However, existing virtual try-on methods frequently encounter challenges, including misalignment between the body and clothing, noticeable artifacts, and the loss of intricate garment details. To overcome these challenges, we introduce a two-stage high-resolution virtual try-on framework that integrates an attention mechanism, comprising a garment warping stage and an image generation stage. During the garment warping stage, we incorporate a channel attention mechanism to effectively retain the critical features of the garment, addressing challenges such as the loss of patterns, colors, and other essential details commonly observed in virtual try-on images produced by existing methods. During the image generation stage, with the aim of maximizing the utilization of the information proffered by the input image, the input features undergo double sampling within the normalization procedure, thereby enhancing the detail fidelity and clothing alignment efficacy of the output image. Experimental evaluations conducted on high-resolution datasets validate the effectiveness of the proposed method. Results demonstrate significant improvements in preserving garment details, reducing artifacts, and achieving superior alignment between the clothing and body compared to baseline methods, establishing its advantage in generating realistic and high-quality virtual try-on images.

关键词： Virtual try-on attention mechanism high-resolution image generation

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A Novel Stacked Network Method for Enhancing the Performance of Side-Channel Attacks

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Computers, Materials & Continua 2025年第4期83卷 1001-1022页

作者： Zhicheng Yin Lang Li Yu Ou College of Computer Science and Technology Hengyang Normal UniversityHengyang421002China Hunan Provincial Key Laboratory of Intelligent Information Processing and Application HengyangNormal UniversityHengyang421002China

The adoption of deep learning-based side-channel analysis(DL-SCA)is crucial for leak detection in secure *** previous studies have applied this method to break targets protected with *** the increasing number of studies,the problem of model *** research mainly focuses on exploring hyperparameters and network architectures,while offering limited insights into the effects of external factors on side-channel attacks,such as the number and type of *** paper proposes a Side-channel Analysis method based on a Stacking ensemble,called *** our method,multiple models are deeply *** the extended application of base models and the meta-model,Stacking-SCA effectively improves the output class probabilities of the model,leading to better ***,this method shows that the attack performance is sensitive to changes in the number of ***,five independent subsets are extracted from the original ASCAD database as multi-segment datasets,which are mutually *** method shows how these subsets are used as inputs for Stacking-SCA to enhance its attack *** experimental results show that Stacking-SCA outperforms the current state-of-the-art results on several considered datasets,significantly reducing the number of attack traces required to achieve a guessing entropy of ***,different hyperparameter sizes are adjusted to further validate the robustness of the method.

关键词： Side-channel analysis deep learning stacking ensemble learning model generalization

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Unified convergence analysis of a second-order method of multipliers for nonlinear conic programming

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Science China mathematics 2022年第11期65卷 2397-2422页

作者： Liang Chen Junyuan Zhu Xinyuan Zhao School of Mathematics Hunan UniversityChangsha 410082China Hunan Provincial Key Laboratory of Intelligent Information Processing and Applied Mathematics Changsha 410082China School of Mathematics Beijing University of TechnologyBeijing 100124China

In this paper,we accomplish the unified convergence analysis of a second-order method of multipliers(i.e.,a second-order augmented Lagrangian method)for solving the conventional nonlinear conic optimization ***,the algorithm that we investigate incorporates a specially designed nonsmooth(generalized)Newton step to furnish a second-order update rule for the *** first show in a unified fashion that under a few abstract assumptions,the proposed method is locally convergent and possesses a(nonasymptotic)superlinear convergence rate,even though the penalty parameter is fixed and/or the strict complementarity ***,we demonstrate that for the three typical scenarios,i.e.,the classic nonlinear programming,the nonlinear second-order cone programming and the nonlinear semidefinite programming,these abstract assumptions are nothing but exactly the implications of the iconic sufficient conditions that are assumed for establishing the Q-linear convergence rates of the method of multipliers without assuming the strict complementarity.

关键词： second-order method of multipliers augmented Lagrangian method convergence rate generalized Newton method second-order cone programming semidefinite programming

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Deep semantic network for hyperspectral image classification using enhanced bifurcation and light self-Gaussian attention mechanism

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Journal of applied Remote Sensing 2025年第1期19卷

作者： Wan, Xiaoqing Chen, Feng He, Yupeng Hengyang Normal University College of Computer Science and Technology Hengyang China Hunan Provincial Key Laboratory of Intelligent Information Processing and Application Hengyang China

Convolutional neural networks (CNNs) are widely used in hyperspectral image (HSI) classification due to their strong feature extraction capabilities. Nevertheless, CNN-based classification methods face challenges in capturing deep semantic features effectively, and as the number of layers increases, computational expenses escalate significantly. In addition, spatial locations and spectral bands in HSI data have varying discriminative power. To address these challenges, we propose a novel approach, DSNet, which integrates a multiway attention mechanism with a CNN-based deep semantic network to improve HSI classification. First, we extract shallow abstract features using a module that combines 3D and 2D convolution layers, followed by transformation through a Gaussian-weighted feature tokenizer. Second, we introduce an enhanced bifurcation attention mechanism with dynamically adjustable perceptual ranges to capture spatial semantic information from both horizontal and vertical perspectives. Third, a convolutional multilayer perceptron module is employed to extract high-level feature representations in both spatial and spectral dimensions, which are then refined by a light self-Gaussian attention module. Finally, a linear layer is used to determine the sample labels. Experiments conducted on three publicly available hyperspectral datasets illustrate that the proposed DSNet achieves superior performance compared with several contemporary state-of-the-art methods, even when trained with limited samples. © 2025 Society of Photo-Optical Instrumentation Engineers (SPIE).

关键词： Convolutional neural networks

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Side-Channel Leakage Analysis of Inner Product Masking

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Computers, Materials & Continua 2024年第4期79卷 1245-1262页

作者： Yuyuan Li Lang Li Yu Ou College of Computer Science and Technology Hengyang Normal UniversityHengyang421002China Hunan Provincial Key Laboratory of Intelligent Information Processing and Application Hengyang Normal UniversityHengyang421002China

The Inner Product Masking(IPM)scheme has been shown to provide higher theoretical security guarantees than the BooleanMasking(BM).This scheme aims to increase the algebraic complexity of the coding to achieve a higher level of *** previous work unfolds when certain(adversarial and implementation)conditions are met,and we seek to complement these investigations by understanding what happens when these conditions deviate from their expected *** this paper,we investigate the security characteristics of IPM under different *** adversarial condition,the security properties of first-order IPMs obtained through parametric characterization are preserved in the face of univariate and bivariate *** implementation condition,we construct two new polynomial leakage functions to observe the nonlinear leakage of the IPM and connect the security order amplification to the nonlinear *** observe that the security of IPMis affected by the degree and the linear component in the leakage *** addition,the comparison experiments from the coefficients,signal-to-noise ratio(SNR)and the public parameter show that the security properties of the IPM are highly implementation-dependent.

关键词： Side-channel analysis inner product masking mutual information nonlinear leakage

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A Review on the Application of Deep Learning Methods in Detection and Identification of Rice Diseases and Pests

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Computers, Materials & Continua 2024年第1期78卷 197-225页

作者： Xiaozhong Yu Jinhua Zheng College of Computer Science and Technology Hengyang Normal UniversityHengyang421002China Hunan Provincial Key Laboratory of Intelligent Information Processing and Application Hengyang Normal UniversityHengyang421002China

In rice production,the prevention and management of pests and diseases have always received special *** methods require human experts,which is costly and *** to the complexity of the structure of rice diseases and pests,quickly and reliably recognizing and locating them is ***,deep learning technology has been employed to detect and identify rice diseases and *** paper introduces common publicly available datasets;summarizes the applications on rice diseases and pests from the aspects of image recognition,object detection,image segmentation,attention mechanism,and few-shot learning methods according to the network structure differences;and compares the performances of existing ***,the current issues and challenges are explored fromthe perspective of data acquisition,data processing,and application,providing possible solutions and *** study aims to review various DL models and provide improved insight into DL techniques and their cutting-edge progress in the prevention and management of rice diseases and pests.

关键词： Deep learning rice diseases and pests image recognition object detection

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