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IEEE/CAA Journal of Automatica Sinica 2024年第3期11卷 690-697页

作者： Yun Zhang Lulu Zhang Yunze Cai the Department of Automation Shanghai Jiao Tong UniversityShanghai 200240 the Key Laboratory of System Control and information Processing Ministry of Education of ChinaShanghai 200240China

This paper presents a novel cooperative value iteration(VI)-based adaptive dynamic programming method for multi-player differential game models with a convergence *** players are divided into two groups in the learning process and adapt their policies *** method removes the dependence of admissible initial policies,which is one of the main drawbacks of the PI-based ***,this algorithm enables the players to adapt their control policies without full knowledge of others’ system parameters or control *** efficacy of our method is illustrated by three examples.

关键词： Adaptive dynamic programming incomplete information multi-player differential game value iteration

3D Localization for Multiple AUVs in Anchor-Free Environments by Exploring the Use of Depth information

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IEEE/CAA Journal of Automatica Sinica 2024年第4期11卷 1051-1053页

作者： Yichen Li Wenbin Yu Xinping Guan the Department of Automation Shanghai Jiao Tong UniversityShanghai 200240 the Key Laboratory of System Control and information Processing Ministry of Education of ChinaShanghai Jiao Tong UniversityShanghai 200240China

Dear Editor,This letter investigates the cooperative localization problem for multiple autonomous underwater vehicles(AUVs)in underwater anchor-free environments,where AUV localization errors grow without bound due to the accumulated errors in inertial measurements(termed accumulated errors hereafter)and the lack of anchors(with known positions).

关键词： AUVs underwater hereafter

Track-before-detect for bistatic radar based on pseudo-spectrum

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Chinese Journal of Aeronautics 2024年第1期37卷 236-246页

作者： Tao HAN Gongjian ZHOU School of Electronics and information Engineering Harbin Institute of TechnologyHarbin 150001China Key Laboratory of Marine Environmental Monitoring and information Processing Ministry of Industry and Information TechnologyHarbin 150001China

Track-Before-Detect(TBD) is an efficient method to detect dim targets for radars. Conventional TBD usually follows an approximate motion model of the target, which may cause an inaccurate integration of the target energy. A TBD technique on basis of pseudo-spectrum in mixed coordinates adopting an accurate motion model for bistatic radar system is developed in this *** predicted position in bistatic polar plane is derived according to a nonlinear function that exactly describes the constant Cartesian velocity motion. Then around the predicted position, a pseudo-spectrum is formulated and its samples are accumulated to the integration frame for energy integration. The evolution of the state and the procedure of accumulation of the target energy are derived elaborately. The superior performance of the proposed method is demonstrated by some simulations.

关键词： Weak target detection Bistatic radar Track-before-detect Pseudo-spectrum Multiframe integration

A Comprehensive Overview of CFN From a Commonsense Perspective

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Machine Intelligence Research 2024年第2期21卷 239-256页

作者： Ru Li Yunxiao Zhao Zhiqiang Wang Xuefeng Su Shaoru Guo Yong Guan Xiaoqi Han Hongyan Zhao Key Laboratory of Computational Intelligence and Chinese information Processing of ministry of Education School of Computer and Information TechnologyShanxi UniversityTaiyuan 030006China

Chinese FrameNet(CFN)is a scenario commonsense knowledge base(CKB)that plays an important role in research on Chinese language *** is based on the theory of frame semantics and English FrameNet(FN).The CFN knowledge base contains a wealth of scenario commonsense knowledge,including frames,frame elements,and frame relations,as well as annotated instances with rich scenario-related labels on Chinese sentences and *** this paper,we conduct a comprehensive overview of CFN from a commonsense perspective,covering topics such as scenario commonsense representation,CFN resources,and its *** also summarize recent breakthroughs and identify future research ***,we introduce the concept of scenario commonsense,including its definitions,examples,and representation methods,with a focus on the relationship between scenario commonsense and the frame concept in *** addition,we provide a comprehensive overview of CFN resources and their applications,highlighting the newly proposed frame-based discourse representation and a human-machine collaboration framework for expanding the CFN ***,we explore emerging topics such as expanding the CFN resource,improving the interpretability of machine reading comprehension,and using scenario CKBs for text generation.

关键词： Chinese FrameNet(CFN) commonsense scenario commonsense frame knowledge

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

Multi-instance partial-label learning: towards exploiting dual inexact supervision

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Science China(information Sciences) 2024年第3期67卷 48-61页

作者： Wei TANG Weijia ZHANG Min-Ling ZHANG School of Computer Science and Engineering Southeast University Key Laboratory of Computer Network and information Integration (Southeast University) Ministry of Education School of information and Physical Sciences The University of Newcastle

Weakly supervised machine learning algorithms are able to learn from ambiguous samples or labels, e.g., multi-instance learning or partial-label learning. However, in some real-world tasks, each training sample is associated with not only multiple instances but also a candidate label set that contains one groundtruth label and some false positive labels. Specifically, at least one instance pertains to the ground-truth label while no instance belongs to the false positive labels. In this paper, we formalize such problems as multi-instance partial-label learning(MIPL). Existing multi-instance learning algorithms and partial-label learning algorithms are suboptimal for solving MIPL problems since the former fails to disambiguate a candidate label set, and the latter cannot handle a multi-instance bag. To address these issues, a tailored algorithm named MIPLGP, i.e., multi-instance partial-label learning with Gaussian processes, is *** first assigns each instance with a candidate label set in an augmented label space, then transforms the candidate label set into a logarithmic space to yield the disambiguated and continuous labels via an exclusive disambiguation strategy, and last induces a model based on the Gaussian processes. Experimental results on various datasets validate that MIPLGP is superior to well-established multi-instance learning and partial-label learning algorithms for solving MIPL problems.

关键词： machine learning multi-instance partial-label learning multi-instance learning partial-label learning Gaussian processes

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Constructing arbitrary self-similar Bessel-like beams via transverse-longitudinal mapping

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Chinese Optics Letters 2024年第2期22卷 167-171页

作者：李岩珂邹昱郭兆金刘圣李鹏魏冰妍温丹丹赵建林 Key Laboratory of Light Field Manipulation and information Acquisition Ministry of Industry and Information TechnologyShaanxi Key Laboratory of Optical Information TechnologySchool of Physical Science and TechnologyNorthwestern Polytechnical UniversityXi’an 710129China

Based on the transverse-longitudinal mapping of Bessel beams,we propose a simple method to construct a self-similar Bessel-like beam whose transverse profile maintains a stretched form during ***,the propagatingvariant width of this beam can be flexibly *** experimentally demonstrate three types of self-similar Bessellike beams whose width variations are linear,piecewise,and period functions of propagation distance,*** experimental results match well with the theoretical *** also demonstrate that our approach enables the generation of self-similar higher-order vortex Bessel-like beams.

关键词： Bessel beams self-similarity transverse-longitudinal mapping

Mutual information oriented deep skill chaining for multi‐agent reinforcement learning

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CAAI Transactions on Intelligence Technology 2024年第4期9卷 1014-1030页

作者： Zaipeng Xie Cheng Ji Chentai Qiao WenZhan Song Zewen Li Yufeng Zhang Yujing Zhang Key Laboratory of Water Big Data Technology of ministry of Water Resources Hohai UniversityNanjingChina College of Computer and information Hohai UniversityNanjingChina Center for Cyber‐Physical Systems University of GeorgiaAthensGeorgiaUSA information Networking Institute Carnegie Mellon UniversityPittsburghPennsylvaniaUSA Department of Electrical and Systems Engineering University of PennsylvaniaPhiladelphiaPennsylvaniaUSA

Multi‐agent reinforcement learning relies on reward signals to guide the policy networks of individual ***,in high‐dimensional continuous spaces,the non‐stationary environment can provide outdated experiences that hinder convergence,resulting in ineffective training performance for multi‐agent *** tackle this issue,a novel reinforcement learning scheme,Mutual information Oriented Deep Skill Chaining(MioDSC),is proposed that generates an optimised cooperative policy by incorporating intrinsic rewards based on mutual information to improve exploration *** rewards encourage agents to diversify their learning process by engaging in actions that increase the mutual information between their actions and the environment *** addition,MioDSC can generate cooperative policies using the options framework,allowing agents to learn and reuse complex action sequences and accelerating the convergence speed of multi‐agent *** was evaluated in the multi‐agent particle environment and the StarCraft multi‐agent challenge at varying difficulty *** experimental results demonstrate that MioDSC outperforms state‐of‐the‐art methods and is robust across various multi‐agent system tasks with high stability.

关键词： artificial intelligence techniques decision making intelligent multi‐agent systems

Spatial Distribution Feature Extraction Network for Open Set Recognition of Electromagnetic Signal

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Computer Modeling in Engineering & Sciences 2024年第4期139卷 279-296页

作者： Hui Zhang Huaji Zhou Li Wang Feng Zhou The ministry Key Laboratory of Electronic information Countermeasure and Simulation Xidian UniversityXi’an710071China Science and Technology on Communication information Security Control Laboratory Jiaxing314033China

This paper proposes a novel open set recognition method,the Spatial Distribution Feature Extraction Network(SDFEN),to address the problem of electromagnetic signal recognition in an open *** spatial distribution feature extraction layer in SDFEN replaces convolutional output neural networks with the spatial distribution features that focus more on inter-sample information by incorporating class center *** designed hybrid loss function considers both intra-class distance and inter-class distance,thereby enhancing the similarity among samples of the same class and increasing the dissimilarity between samples of different classes during ***,this method allows unknown classes to occupy a larger space in the feature *** reduces the possibility of overlap with known class samples and makes the boundaries between known and unknown samples more ***,the feature comparator threshold can be used to reject unknown *** signal open set recognition,seven methods,including the proposed method,are applied to two kinds of electromagnetic signal data:modulation signal and real-world *** experimental results demonstrate that the proposed method outperforms the other six methods overall in a simulated open ***,compared to the state-of-the-art Openmax method,the novel method achieves up to 8.87%and 5.25%higher micro-F-measures,respectively.

关键词： Electromagnetic signal recognition deep learning feature extraction open set recognition

Mutual aid instead of mutual restraint:interactive probing for topological charge and phase of a vortex beam of large aberrations

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Photonics Research 2024年第1期12卷 172-182页

作者： SHENGYANG WU BENLI YU LEI ZHANG Key Laboratory of Opto-electronic information Acquisition and Manipulation Ministry of EducationAnhui UniversityHefei 230601China information Materials and Intelligent Sensing Laboratory of Anhui Province Anhui UniversityHefei 230601China

An imperfect propagation environment or optical system would introduce wavefront aberrations to vortex *** phase aberrations and orbital angular momentum in a vortex beam are proved to be mutually restrictive in parameter *** make traditional topological charge(TC)probing methods ineffective while the phase singularity makes phase retrieval difficult due to the aliasing between the wrapped phase jump and the vortex phase *** interactive probing method is proposed to make measurements of the aberrated phase and orbital angular momentum in a vortex beam assist rather than hinder each *** phase unwrapping is liberated from the phase singularity by an annular shearing interference technique while the TC value is determined by a Moirétechnique immune to *** and experimental results proving the method effective are *** is of great significance to judge the characteristics of vortex beams passing through nonideal environments and optical systems.

关键词： vortex topological beam