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On-chip spiking neural networks based on add-drop ring microresonators and electrically reconfigurable phase-change material photonic switches

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Photonics Research 2024年第4期12卷 755-766页

作者： QIANG ZHANG NING JIANG YIQUN ZHANG ANRAN LI HUANHUAN XIONG GANG HU YONGSHENG CAO KUN QIU school of information and Communication Engineering University of Electronic Science and Technology of ChinaChengdu 611731China

We propose and numerically demonstrate a photonic computing primitive designed for integrated spiking neural networks (SNNs) based on add-drop ring microresonators (ADRMRs) and electrically reconfigurable phasechange material (PCM) photonic switches. In this neuromorphic system, the passive silicon-based ADRMR,equipped with a power-tunable auxiliary light, effectively demonstrates nonlinearity-induced dual neural dynamics encompassing spiking response and synaptic plasticity that can generate single-wavelength optical neural spikes with synaptic weight. By cascading these ADRMRs with different resonant wavelengths, weighted multiple-wavelength spikes can be feasibly output from the ADRMR-based hardware arrays when external wavelengthaddressable optical pulses are injected;subsequently, the cumulative power of these weighted output spikes is utilized to ascertain the activation status of the reconfigurable PCM photonic switches. Moreover, the reconfigurable mechanism driving the interconversion of the PCMs between the resonant-bonded crystalline states and the covalent-bonded amorphous states is achieved through precise thermal modulation. Drawing from the thermal properties, an innovative thermodynamic leaky integrate-and-firing (TLIF) neuron system is proposed. With the TLIF neuron system as the fundamental unit, a fully connected SNN is constructed to complete a classic deep learning task:the recognition of handwritten digit patterns. The simulation results reveal that the exemplary SNN can effectively recognize 10 numbers directly in the optical domain by employing the surrogate gradient algorithm. The theoretical verification of our architecture paves a whole new path for integrated photonic SNNs, with the potential to advance the field of neuromorphic photonic systems and enable more efficient spiking information processing.

关键词： neural networks precise

Probabilistic modeling of multifunction radars with autoregressive kernel mixture network

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Defence technology（防务技术） 2024年第5期35卷 275-288页

作者： Hancong Feng Kaili.Jiang Zhixing Zhou Yuxin Zhao Kailun Tian Haixin Yan Bin Tang school of information and Communication Engineering University of Electronic Science and Technology of ChinaChengdu 611731China

The task of modeling and analyzing intercepted multifunction radars(MFRs)pulse trains is vital for cognitive electronic *** methodologies predominantly rely on prior information or heavily constrained models,posing challenges for non-cooperative *** paper introduces a novel approach to model MFRs using a Bayesian network,where the conditional probability density function is approximated by an autoregressive kernel mixture network(ARKMN).Utilizing the estimated probability density function,a dynamic programming algorithm is proposed for denoising and detecting change points in the intercepted MFRs pulse *** results affirm the proposed method's efficacy in modeling MFRs,outperforming the state-of-the-art in pulse train denoising and change point detection.

关键词： Probabilistic forecasting Multifunction radar Unsupervised learning Change point detection Outlier detection

SAC-Based Computation Offloading for Reconfigurable Intelligent Surface-Aided Mobile Edge Networks

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China Communications 2024年第6期21卷 261-270页

作者： Li Bin Qian Zhen Fei Zesong school of Computer science Nanjing University of Information Science&TechnologyNanjing 210044China Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment technology(CICAEET) Nanjing University of Information Science&TechnologyNanjing 210044 school of information and Electronics Beijing Institute of TechnologyBeijing 100081China

In this paper,we concentrate on a reconfigurable intelligent surface(RIS)-aided mobile edge computing(MEC)system to improve the offload efficiency with moving user equipments(UEs).We aim to minimize the energy consumption of all UEs by jointly optimizing the discrete phase shift of RIS,UEs’transmitting power,computing resources allocation,and the UEs’task offloading strategies for local computing and *** formulated problem is a sequential decision making across multiple coherent time ***,the mobility of UEs brings uncertainties into the decision-making *** cope with this challenging problem,the deep reinforcement learning-based Soft Actor-Critic(SAC)algorithm is first proposed to effectively optimize the discrete phase of RIS and the UEs’task offloading ***,the transmitting power and computing resource allocation can be determined based on the *** results demonstrate that the proposed algorithm can be trained more stably and perform approximately 14%lower than the deep deterministic policy gradient benchmark in terms of energy consumption.

关键词： MEC RIS soft actor-critic user mobility

Frequency-tunable single-photon router based on a microresonator containing a driven three-level emitter

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Chinese Physics B 2024年第6期33卷 377-381页

作者：黄劲松胡菁兰李艳玲徐中辉 school of information Engineering Jiangxi University of Science and TechnologyGanzhou 341000China Faculty of science Jiangxi University of Science and TechnologyGanzhou 341000China

We propose a frequency-tunable router of single photons with high routing efficiency, which is constructed by two waveguides mediately linked by a single-mode whispering gallery resonator with a driven three-level emitter. Quantum routing probability in the output port is obtained via the real-space Hamiltonian. By adjusting the resonator–emitter coupling and the drive, the desired continuous central frequencies for the resonance peaks of routing photons can be manipulated nearly linearly, with the assistance of Rabi splitting effect and optical Stark shift. The proposed routing system may provide potential applications in designing other frequency-modulation quantum optical devices, such as multiplexers,filters, and so on.

关键词： quantum routing scattering theory optical waveguide microresonator

CrossFormer Embedding DeepLabv3+ for Remote Sensing Images Semantic Segmentation

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Computers, Materials & Continua 2024年第4期79卷 1353-1375页

作者： Qixiang Tong Zhipeng Zhu Min Zhang Kerui Cao Haihua Xing school of information science and technology Hainan Normal UniversityHaikou571158China

High-resolution remote sensing image segmentation is a challenging task. In urban remote sensing, the presenceof occlusions and shadows often results in blurred or invisible object boundaries, thereby increasing the difficultyof segmentation. In this paper, an improved network with a cross-region self-attention mechanism for multi-scalefeatures based onDeepLabv3+is designed to address the difficulties of small object segmentation and blurred targetedge segmentation. First,we use CrossFormer as the backbone feature extraction network to achieve the interactionbetween large- and small-scale features, and establish self-attention associations between features at both large andsmall scales to capture global contextual feature information. Next, an improved atrous spatial pyramid poolingmodule is introduced to establish multi-scale feature maps with large- and small-scale feature associations, andattention vectors are added in the channel direction to enable adaptive adjustment of multi-scale channel *** proposed networkmodel is validated using the PotsdamandVaihingen datasets. The experimental results showthat, compared with existing techniques, the network model designed in this paper can extract and fuse multiscaleinformation, more clearly extract edge information and small-scale information, and segment boundariesmore smoothly. Experimental results on public datasets demonstrate the superiority of ourmethod compared withseveral state-of-the-art networks.

关键词： Semantic segmentation remote sensing multiscale self-attention

Contrastive Consistency and Attentive Complementarity for Deep Multi-View Subspace Clustering

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Computers, Materials & Continua 2024年第4期79卷 143-160页

作者： Jiao Wang Bin Wu Hongying Zhang school of information Engineering Southwest University of Science and TechnologyMianyang621010China

Deep multi-view subspace clustering (DMVSC) based on self-expression has attracted increasing attention dueto its outstanding performance and nonlinear application. However, most existing methods neglect that viewprivatemeaningless information or noise may interfere with the learning of self-expression, which may lead to thedegeneration of clustering performance. In this paper, we propose a novel framework of Contrastive Consistencyand Attentive Complementarity (CCAC) for DMVsSC. CCAC aligns all the self-expressions of multiple viewsand fuses them based on their discrimination, so that it can effectively explore consistent and complementaryinformation for achieving precise clustering. Specifically, the view-specific self-expression is learned by a selfexpressionlayer embedded into the auto-encoder network for each view. To guarantee consistency across views andreduce the effect of view-private information or noise, we align all the view-specific self-expressions by contrastivelearning. The aligned self-expressions are assigned adaptive weights by channel attention mechanism according totheir discrimination. Then they are fused by convolution kernel to obtain consensus self-expression withmaximumcomplementarity ofmultiple views. Extensive experimental results on four benchmark datasets and one large-scaledataset of the CCAC method outperformother state-of-the-artmethods, demonstrating its clustering effectiveness.

关键词： Deep multi-view subspace clustering contrastive learning adaptive fusion self-expression learning

QoS-Aware Computation Offloading in LEO Satellite Edge Computing for IoT:A Game-Theoretical Approach

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Chinese Journal of Electronics 2024年第4期33卷 875-885页

作者： Ying CHEN Jintao HU Jie ZHAO Geyong MIN school of Computer science Beijing Information Science and Technology University University of Exeter

Low earth orbit(LEO) satellite edge computing can overcome communication difficulties in harsh environments, which lack the support of terrestrial communication infrastructure. It is an indispensable option for achieving worldwide wireless communication coverage in the future. To improve the quality-of-service(QoS) for Internet-of-things(IoT) devices, we combine LEO satellite edge computing and ground communication systems to provide network services for IoT devices in harsh environments. We study the QoS-aware computation offloading(QCO) problem for IoT devices in LEO satellite edge computing. Then we investigate the computation offloading strategy for IoT devices that can minimize the total QoS cost of all devices while satisfying multiple constraints, such as the computing resource constraint, delay constraint, and energy consumption constraint. We formulate the QoSaware computation offloading problem as a game model named QCO game based on the non-cooperative competition game among IoT devices. We analyze the finite improvement property of the QCO game and prove that there is a Nash equilibrium for the QCO game. We propose a distributed QoS-aware computation offloading(DQCO) algorithm for the QCO game. Experimental results show that the DQCO algorithm can effectively reduce the total QoS cost of IoT devices.

关键词： Satellites Costs Computational modeling Low earth orbit satellites Quality of service Games Nash equilibrium

Weighted Linear Loss Large Margin Distribution Machine for Pattern Classification

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Chinese Journal of Electronics 2024年第3期33卷 753-765页

作者： Ling LIU Maoxiang CHU Rongfen GONG Liming LIU Yonghui YANG school of Electronic and information Engineering University of Science and Technology Liaoning

Compared with support vector machine,large margin distribution machine(LDM) has better generalization *** central idea of LDM is to maximize the margin mean and minimize the margin variance *** the computational complexity of LDM is *** order to reduce the computational complexity of LDM,a weighted linear loss LDM(WLLDM) is *** framework of WLLDM is built based on LDM and the weighted linear *** weighted linear loss is adopted instead of the hinge loss in *** modification can transform the quadratic programming problem into a simple linear equation,resulting in lower computational ***,WLLDM has the potential to deal with large-scale *** WLLDM is similar in principle to the LDM algorithm,which can optimize the margin distribution and achieve better generalization *** WLLDM algorithm is compared with other models by conducting experiments on different *** results show that the proposed WLLDM has better generalization performance and faster training speed.

关键词： Training Support vector machines Pattern classification Transforms Fasteners Mathematical models Vectors

Flexible incidence angle scanning surface plasmon resonance microscopy for morphology detection with enhanced contrast

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Photonics Research 2024年第6期12卷 1213-1221页

作者： LINGKE WANG JINGYU MI SHUQI WANG WENRUI LI JU TANG JIAWEI ZHANG JIWEI ZHANG JIANLIN ZHAO Key Laboratory of Light Field Manipulation and information Acquisition Ministry of Industry and Information Technologyand Shaanxi Key Laboratory of Optical Information TechnologySchool of Physical Science and TechnologyNorthwestern Polytechnical UniversityXi’an 710129China

Surface plasmon resonance microscopy(SPRM)has been massively applied for near-field optical measurement,sensing,and imaging because of its high detection sensitivity,nondestructive,noninvasive,wide-field,and label-free imaging ***,the transverse propagation characteristic of the surface plasmon wave generated during surface plasmon resonance(SPR)leads to notable“tail”patterns in the SPR image,which severely deteriorates the image ***,we propose an incidence angle scanning method in SPRM to obtain a resonance angle image with exceptional contrast that significantly mitigates the adverse effects of“tail”*** resonance angle image provides the complete morphology of the analyzed samples and enables two-dimensional quantification,which is incapable in conventional *** effectiveness of the method was experimentally verified using photoresist square samples with different sizes and two-dimensional materials with various geometric *** edges of samples were fully reconstructed and a maximum fivefold increase in the image contrast has been *** method offers a convenient way to enhance the SPRM imaging capabilities with low cost and stable performance,which greatly expands the applications of SPRM in label-free detection,imaging,and quantification.

关键词： angle resonance surface