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Lecture Notes in Control and Information Sciences 2023年 492卷 v-vi页

作者： Luan, Xiaoli He, Shuping Liu, Fei Key Laboratory of Advanced Process Control for Light Industry [Ministry of Education Institute of Automation Jiangnan University Jiangsu Wuxi China Key Laboratory of Intelligent Computing and Signal Processing [Ministry of Education School of Electrical Engineering and Automation Anhui University Anhui Hefei China

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Meta Network for Radar HRRP Noncooperative Target Recognition with Missing Aspects

Meta Network for Radar HRRP Noncooperative Target Recognitio...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Long Tian Bo Chen Yang Peng Chuan Du Zhenhua Wu Hongwei Liu National Laboratory of Radar Signal Processing Xidian University Xi'an China School of Electronics and Communication Engeering Sun Yat-sen University Guangzhou China Key Laboratory of Intelligent Computing and Signal Processing Anhui University Hefei China

ISBN: (数字)9781728163741

ISBN: (纸本)9781728163758

We propose a meta network (MNet) for the problem of target-aspect missing in radar high-resolution range profile (HRRP)-based noncooperative target recognition, where a classifier must be generalized to new aspects not seen in the training set, given only a small number of HRRP data of each new aspect. The MNet is a time domain convolutional neural network (TCNN) that is built based upon recent progress in meta-learning. In effect, it learns a model that is easy and fast to fine-tune, allowing the adaptation to happen in the right space for fast learning. Besides, we construct a new controllable HRRP dataset suitable for the scenario of noncooperative target-aspect missing using electromagnetic simulation. Compared with the traditional methods, the MNet is more efficient and could achieve better performance. Extensive experiments on the simulated HRRP dataset are conducted to illustrate the effectiveness of the proposed method.

关键词： Task analysis Training Target recognition Radar Adaptation models Time-domain analysis Solid modeling

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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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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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Cavity-Quantum Electrodynamics with Moiré Flatband Photonic Crystals

arXiv

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arXiv 2024年

作者： Wang, Yu-Tong Ye, Qi-Hang Yan, Jun-Yong Qiao, Yufei Chen, Chen Cheng, Xiao-Tian Li, Chen-Hui Zhang, Zi-Jian Huang, Cheng-Nian Meng, Yun Zou, Kai Zhan, Wen-Kang Zhao, Chao Hu, Xiaolong Tee, Clarence Augustine T.H. Sha, Wei E.I. Huang, Zhixiang Liu, Huiyun Jin, Chao-Yuan Ying, Lei Liu, Feng State Key Laboratory of Extreme Photonics and Instrumentation College of Information Science and Electronic Engineering Zhejiang University Hangzhou310027 China School of Physics Zhejiang Key Laboratory of Micro-nano Quantum Chips and Quantum Control Zhejiang University Hangzhou310027 China School of Precision Instrument and Optoelectronic Engineering Tianjin University Tianjin300072 China Key Laboratory of Optoelectronic Information Science and Technology Ministry of Education Tianjin300072 China Laboratory of Solid State Optoelectronics Information Technology Institute of Semiconductors Chinese Academy of Sciences Beijing100083 China College of Materials Science and Opto-Electronic Technology University of Chinese Academy of Science Beijing101804 China College of Physics and Electrical Information Engineering Zhejiang Normal University Hangzhou310058 China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei230039 China Department of Electronic and Electrical Engineering University College London LondonWC1E 7JE United Kingdom International Joint Innovation Center Zhejiang University Haining314400 China

Quantum emitters are a key component in photonic quantum technologies. Enhancing their single-photon emission by engineering the photonic environment using cavities can improve the overall efficiency in quantum information processing. However, this enhancement is often limited by the need for precise nanoscale control over emitter’s position within micro/nano-cavities. Inspired by the fascinated physics of moiré pattern, we present an approach to strongly modify the spontaneous emission rate of a quantum emitter using fine-designed multilayer moiré photonic crystal with a robust isolate-flatband dispersion. Theoretical analysis reveals that due to its nearly infinite photonic density of states, the moiré cavity can simultaneously possess high Purcell factor and large tolerance over emitter’s position. We experimentally demonstrate the coupling between this moiré cavity and a quantum dot via the cavity-determined polarization of the dot’s emission. The radiative lifetime of the quantum dot can be tuned by a factor of 40 from 42 ps to 1692 ps, attributed to strong Purcell enhancement and Purcell inhibition effects. Our findings pave the way for moiré flatband cavity-enhanced quantum light sources, quantum optical switches and quantum nodes for quantum internet. Copyright © 2024, The Authors. All rights reserved.

关键词： Particle beams

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Control of space-dependent four-wave mixing in a four-level atomic system

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Physical Review A 2020年第3期102卷 033516-033516页

作者： Jing Qiu Zhiping Wang Dongsheng Ding Zhixiang Huang Benli Yu Key Laboratory of Opto-Electronic Information Acquisition and Manipulation Ministry of Education Anhui University Hefei 230601 China Key Laboratory of Quantum Information University of Science and Technology of China Hefei Anhui 230026 China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei 230039 China

We propose a scheme to demonstrate the manipulation of space-dependent four-wave mixing (FWM) in a four-level atomic system. By adjusting the detuning of the control field, one can effectively control the FWM output field transferred from a pump beam carrying orbital angular momentum. More interestingly, by appropriate choice of the intensity of the control field, the FWM field can be significantly enhanced and phase twist is almost completely suppressed. Furthermore, the superposition modes created by the interference between the FWM field and a same-frequency Gaussian beam are also discussed, showing many interesting properties. Our results may open some possibilities for phase imprinting in Bose-Einstein condensates or atom manipulation with optical tweezers.

关键词： Angular momentum of light Atom optics Coherent control Optical coherence

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Improved Matrix-based Attribute Reduction Algorithm Based on Minimal Elements for Mobile Edge computing

Improved Matrix-based Attribute Reduction Algorithm Based on...

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IEEE/ACM International Symposium on Cluster computing and the Grid (CCGRID)

作者： Yi Xu Zhiqiang Zheng Yan Cheng Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei China School of Computer Science and Technology Anhui University Hefei China

ISBN: (数字)9781728160955

ISBN: (纸本)9781728196497

With the development of Internet of Thlngs(IoT) technology, the Mobile Edge computing (MEC) environment plays an important role in different scenarios. This paper focus on the "last-mile" delivery scenario in logistics. In this scenario, due to the limited computation ability of the unmanned aerial vehicle (UAV), high real-time and computational resource-intensive tasks such as obstacle avoidance, route planning, and face recognition are require the assistance by MEC computing resources. However, due to the limited computing power of edge servers, the computing tasks of neural networks has very high delay. It cause the deadline of neural networks computation task may not be satisfied. Besides with the users and environment changed continuously, the neural nework take a long time to update which may affect the work of UAV. Therefore, It is an critical problem to accelerate the calculation and update of neural network on edge server. This paper proposes an attribute reduction algorithm based on rough set, which can reduce redundant attributes and compress the dimensionality of data. The experimental results show that can accelerate the calculation and update of neural network significantly and save the energy consumption.

关键词： Servers Edge computing Task analysis Neural networks Energy consumption Information systems Rough sets

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Semantic Based Heterogeneous Information Network Embedding for Patent Citation Recommendation

Semantic Based Heterogeneous Information Network Embedding f...

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Artificial Intelligence and Computer Engineering (ICAICE), International Conference on

作者： Yanping Zhang Shuang Li Xi Chen Fulan Qian Shu Zhao Shuwei Zhu Yulu Wang Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei China School of Computer Science and Technology Anhui University Hefei China

ISBN: (数字)9781728191461

ISBN: (纸本)9781728191478

With the increasing number of patents, the task of patent citation recommendation becomes more and more important and meaningful. The core of a patent is textual content, which describes technical ideas and scope of the protection. Therefore, most of the existing patent citation recommendation methods focus on textual content. Recently, some scholars introduce bibliographic (structural) data to construct heterogeneous information network (HIN) on the basis of textual content to further improve the effect of recommendation. Most of these methods build HIN directly based on candidate patents selected in advance according to text similarity, which simplifies the complexity of the problem. However, the latent semantic relationships between patents formed by the textual content are often ignored, which can be used to mine more semantic and structural relationships in HIN. In this paper, in order to capture deep semantic and structural information, we introduce Semantic based Heterogeneous Information Network Embedding (SHINE) which obtains the latent semantic relationships between patents (referred to as semantic links in this paper) by textual content similarity and topic similarity, and links the semantic relationships with network structure to build a novel HIN. First, to obtain semantic links, we not only consider the textual content similarity between patents but also the topic similarity. We use the linear fusion method to combine these two similarities. Secondly, we build a HIN with semantic links and bibliographic information to integrate semantic and structural information, and we use network embedding to map the integration of two kinds of information into a common vector space. Finally, we recommend patent citations by linear combination of multi-modal similarities. The experimental results on two U.S. patent datasets show the effectiveness of SHINE. Compared to state-of-the art of patent citation recommendation, the proposed method SHINE achieves significantl

关键词： Patents Art Computational modeling Semantics Complexity theory Task analysis Artificial intelligence

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Local Smoothing Optimization Penalized Least Squares: Application to Spectrum Baseline Correction

Local Smoothing Optimization Penalized Least Squares: Applic...

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第31届中国过程控制会议（CPCC 2020）

作者： Yuqiang Li Tianhong Pan Haoran Li Shan Chen Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Electrical Engineering and Automation Anhui University School of Electrical and Information Engineering Jiangsu University

Baseline shift, as an undesirable component of processing signal, seriously contaminates the essential information of the analysis object and deteriorates the performance of the developed model. The baseline correction methods based on penalized least squares have been widely applied in various industries and obtained better results in the single interval signal. However, the real analyzed signal is composed of multiple intervals with different smoothness, and the current baseline correction methods using constant smoothing parameters throughout the process cannot eliminate the baseline of the multi-interval signal. To address this issue, a local smoothing optimization penalized least squares(lsoPLS) method is presented in this work. The local smoothing optimization strategy using the derivative difference between the previously fitted baseline and the original signal is used to identify the interval location, while smoothing parameter is optimized by the interval characteristics. Two simulated cases and one real experiment were used to evaluate the effectiveness of the proposed lsoPLS method. Experimental results confirm that the proposed method has better performance in the multi-interval baseline correction and can be served as an effective pre-processing method for the complex spectral signal.

关键词： Baseline correction local smoothing optimization penalized least square signal pre-processing spectral analysis

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