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An ultra-wideband pattern reconflgurable antenna based on graphene coating

Chinese Physics B 2016年第11期25卷 625-631页

作者：姜彦南袁锐高喜王娇李思敏林诒玉 Guangxi Key Laboratory of Wireless Wideband Communication and Signal Processing Guilin 541004 China Key Laboratory of Cognitive Radio and Information Processing (Ministry of Education) Guilin University of Electronic Technology Guilin 541004 China Guangxi Experiment Center of Information Science Guilin University of Electronic Technology Guilin 541004 China

An ultra-wideband pattern reconfigurable antenna is *** antenna is a dielectric coaxial hollow monopole with a cylindrical graphene-based impedance surface *** consists of a graphene sheet coated onto the inner surface of a cylindrical substrate and a set of independent polysilicon DC gating pads mounted on the outside of the cylindrical *** changing the DC bias voltages to the different gating pads,the surface impedance of the graphene coating can be freely *** to the tunability of graphene＇s surface impedance,the radiation pattern of the proposed antenna can be reconfigured.A transmission line method is used to illustrate the physical mechanism of the proposed *** results show that the proposed antenna can reconfigure its radiation pattern in the omnidirectional mode with the relative bandwidth of 58.5% and the directional mode over the entire azimuth plane with the relative bandwidth of 67%.

关键词： wideband antenna impedance bandwidth directional illustrate hollow dielectric coated outside

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Reconstruct LDPC Codes in a Noisy Environment

Reconstruct LDPC Codes in a Noisy Environment

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2015 IEEE International Conference on Progress in Informatics and Computing(PIC 2015)

作者： Xin Bao Yuanling Huang Guiliang Wang National Key Laboratory of Science and Technology on Blind Signal Processing

Focus on the problem of reconstructing LDPC codes in a noisy environment, an algorithm based on Column Elimination Operation, Parity-Check Vector Judgment Criterion and Gradual Row Transformation is proposed, which is used to blind recognize LDPC codes. This algorithm first gets enough dual vectors of the receive codes, then selects real parity-check vectors of the dual-space of LDPC codes, and then, detectives and deletes the error code words. The above steps are iteratively carried out until the original problem is reduced to an easier problem, i.e., blind recognition LDPC codes in an error-free context, and finally obtain the sparse parity-check matrix by using Gradual Row Transformation. The simulation and experiment results show that, this algorithm fits most of LDPC standards, including 802.16 e, 802.11 n, DVB-S2, GJB7296, GB20600, etc., and it is an effective solution for LDPC codes blind recognition in a noisy environment.

关键词： channel coding LDPC codes blind recognition error bit

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Numerical Simulation of Viscous Cavitating Flow Around A Ship Propeller

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China Ocean Engineering 2011年第3期25卷 539-548页

作者：朱志峰方世良王晓燕孟昭文刘平香杜选民 Key Laboratory of Underwater Acoustic Signal Processing of Ministry of Education Southeast University School of Electrical Engineering and Information Anhui University of Technology Science and Technology on Acoustic Antagonizing Laboratory Shanghai Marine ElectronicEquipment Research Institute

In the present study, cavitation and a ship propeller wake are reported by computed fluid dynamics based on viscous multiphase flow theory. Some recent validation results with a hybrid grid based on unsteady Navier-Stokes （N-S） and bubble dynamics equations are presented to predict velocity, pressure and vapor volume fraction in propeller wake in a uniform inflow. Numerical predictions of sheet cavitation, tip vortex cavitation and hub vortex cavitation are in agreement with the experimental data, same as numerical predictions of longitudinal and transversal evolution of the axial velocity. Blade and shaft rate frequency of propeller is well predicted by the computed results of pressure, and tip vortex is the most important to generate the pressure field within the near wake. The overall results indicate that the present approach is reliable for prediction of cavitation and propeller wake on the condition of uniform inflow.

关键词： cavitatingflow RANS propeller sliding mesh multiphaseflow

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A Self-Adaptive Modified Whale Optimization Algorithm for Optimizing the Linear Antenna Array

A Self-Adaptive Modified Whale Optimization Algorithm for Op...

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International Conference on Measuring technology and Mechatronics Automation, ICMTMA

作者： Wentao Feng Kekang Song National Key Laboratory of Science and Technology on Blind Signal Processing Chengdu China National Key Laboratory of Science and Technology on Blind Signal Processing Sichuan Chengdu China

ISBN: (数字)9781728170817

ISBN: (纸本)9781728170824

The whale optimization algorithm (WOA) is an effective algorithm for solving complex optimization problem. Its unique search mechanism results in better exploitation than exploration capability which means that it's easy to get trapped in the local optima. A self-adaptive modified whale optimization algorithm named of SAMWOA is proposed. A self-adaptive quasi-opposition method and novel population updating mechanism is integrated into the whale optimization algorithm to improve the solution accuracy. Finally, the proposed algorithm is utilized in optimizing the radiation pattern of a 16-element linear antenna array. The experimental results show that SAMWOA algorithm can reduce the sidelobe level obviously.

关键词：

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Robust adaptive beamforming based on calibrated covariance matrix reconstruction 2

Robust adaptive beamforming based on calibrated covariance m...

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2nd International Conference on Communication and Information Systems, ICCIS 2017

作者： Liankun, Bo Jinyu, Xiong Chengyuan, Liu Science and technology on blind signal proceΒing laboratory P.O. Box 393 Chengdu China

ISBN: (纸本)9781450353489

Adaptive beamformers will suffer performance degradation when a model mismatch exists. For the beamformers based on interference-plus-noise covariance matrix (INCM) reconstruction, the random sensor position perturbation will result in a poor output signal-to-noise-plus-interference ratio (SINR). In this paper, a robust adaptive beamformer based on calibrated INCM reconstruction is proposed. The principle is to calibrate the Capon spectrum and array steering vector (ASV) by using the first order approximation model of perturbed ASV. The INCM is reconstructed by integrating the calibrated Capon spectrum over an angular sector which excludes the signal-of-interest (SOI), and the ASV of SOI is reestimated by using the projection technique, where the projection matrix is formed from the eigenvector analysis of the reconstructed INCM. Simulation results indicate that the proposed beamformer has a more superior performance against random sensor position perturbation in a wide range of signal-to-noise ratio (SNR) than other beamformers. © 2017 AΒociation for Computing Machinery.

关键词： signal to noise ratio

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Degradation-Trend-Aware Deep Neural Network with Attention Mechanism for Bearing Remaining Useful Life Prediction

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第6期5卷 2997-3011页

作者： Liu, Yongkang Pan, Donghui Zhang, Haifeng Zhong, Kai Anhui University Key Laboratory of Intelligent Computing and Signal Processing of the Ministry of Education School of Mathematical Sciences Hefei230601 China Anhui University Key Laboratory of Intelligent Computing and Signal Processing of the Ministry of Education Institutes of Physical Science and Information Technology Hefei230601 China

Remaining useful life (RUL) prediction of bearings has extraordinary significance for prognostics and health management (PHM) of rotating machinery. RUL prediction approaches based on deep learning have been dedicated to finding a nonlinear mapping relationship between nonstationary monitoring data and RUL. However, most existing approaches pay little attention to the degradation trend of diverse health stages of bearing and lack the discriminative power of crucial degradation features, resulting in the loss of some important information associated with RUL. To address this challenge, this article proposes a novel RUL prediction framework based on degradation-trend-aware deep neural network with attention mechanism (DTADAN). First the multidirection features with evident degradation trend are extracted via the analysis of bearing vibration signal from both time-domain and time-frequency domain. Next, the deep neural network architecture with attention mechanism is utilized to adaptively learn the critical degradation features beneficial for RUL prediction. Distinct from the existing approaches, the proposed framework is able to dynamically extract key degradation features of the bearing including degradation trend information and effectively fuse multidirection information to improve RUL prediction accuracy. The performance of the proposed approach is evaluated via case studies on XJTU-SY bearing dataset and PRONOSTIA bearing dataset. Compared with other state-of-the-art approaches, the proposed framework has better predictive accuracy and robustness. Additionally, interpretable analysis is provided to reveal the process of model learning and data characteristics, and the analysis results are helpful in guiding model learning. © 2020 IEEE.

关键词： Deep neural networks

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A data-assisted adaptive detection algorithm for shortwave burst signals 5

A data-assisted adaptive detection algorithm for shortwave b...

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5th International Conference on Advanced Electronic Materials, Computers and Software Engineering, AEMCSE 2022

作者： Yi Wei, Feng Wen Zhong, Qu Yan, Zhao Yu Mei, Zhou Pla Strategic Support Force Information Engineering University College of Information System Engineering Zhengzhou China National Key Laboratory of Science and Technology on Blind Signal Processing Chengdu China

ISBN: (数字)9781665484749

ISBN: (纸本)9781665484749

For shortwave signals with unique code frame structure, a data-assisted adaptive burst detection algorithm is proposed in this paper. The algorithm weakens the high bottom-noise undulation of signal correlation values due to shortwave channel fading by using a locally normalized sliding differential correlation. Also based on this, an adaptive gate limit detection strategy based on sliding window comparison judgments is used to improve the burst detection accuracy. This paper focuses on the effects of signal-to-noise ratio and shortwave channel environment on the performance of this algorithm, and simulation experiments are conducted under different conditions. The simulation results show that the algorithm has good robustness and can still achieve good detection results in the case of low signal-to-noise ratio as well as short-wave poor channels. © 2022 IEEE.

关键词： Fading channels

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Speech language classification algorithm based on multiple-instance learning with negative sample cleaning 9

Speech language classification algorithm based on multiple-i...

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9th IEEE Joint International Information technology and Artificial Intelligence Conference, ITAIC 2020

作者： Zhang, Jianyi Xu, Wei Yao, Jiaqi Yan, Jikun Huang, Xin PLA Strategic Support Force Information Engineering University College of Information System Engineering Zhengzhou China National Key Laboratory of Science and Technology on Blind Signal Processing Chengdu China

Speech language classification is an important direction in the field of machine learning. In order to further improve the effect of speech classification, this paper propose a new speech language classification algorithm based on multiple-instance learning with negative instance cleaning, namely NUMI-Biased SVM algorithm. Firstly, extract MFCC features from speech files, regarding each file as an instance bag, and every speech frame as an instance. Secondly, adopt PU learning algorithm to clean negative instances in positive bags to reduce their impact on classification. Finally, multiple-instance learning algorithm is used to classify the speech files. Experiments show that, compared with the SVM algorithm and multiple-instance SVM algorithm, NUMI-Biased-SVM has achieved significant improvement in classification performance. © 2020 IEEE.

关键词： Speech

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Multi-Node Collaborative Resource Allocation Method for Concurrent Tasks

Multi-Node Collaborative Resource Allocation Method for Conc...

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2022 IEEE International Conference on Unmanned Systems, ICUS 2022

作者： Zhu, Mingjun Huang, Yuanling Ji, Xiaoting Luo, Yanpeng Cheng, Haibing Zhang, Tongxin School of Information System Engineering Pla Strategic Support Force Information Engineering University Zhengzhou China National Key Laboratory of Science and Technology on Blind Signal Processing Chengdu China

ISBN: (数字)9781665484565

ISBN: (纸本)9781665484565

Current unmanned aerial vehicle (UAV) and their mission system have been gradually developed in the direction of swarming together. However, the existing swarm coordination method usually realizes the parallel execution of multiple tasks through the assignment missions for various nodes, so the number of concurrent missions supported by the system is minimal, which is challenging to meet the requirements of electromagnetic monitoring tasks in the natural electromagnetic environment. Therefore, this paper introduces the idea of time-division multiplexing and proposes a time resource allocation algorithm for concurrent tasks oriented to multi-node synchronous cooperation. Based on the fixed-priority scheduling strategy, the algorithm can reasonably schedule sensor resources of each UAV node according to priority constraints, which improves the concurrent task processing capability of the UAV swarm. Through the fast schedulability test based on blocking interval, the task's parameters can be adjusted quickly to ensure the mission's correct execution and improve the UAV swarm's dynamic adaptability. Finally, simulation verifies the proposed algorithm's effectiveness and feasibility. © 2022 IEEE.

关键词： Time division multiplexing

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Research on Target Detection Based on Clustering and Hough Transform

Research on Target Detection Based on Clustering and Hough T...

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2022 International Conference on Statistics, Data science, and Computational Intelligence, CSDSCI 2022

作者： Luo, Yanpeng Xiong, Jinyu Yang, Yuxiang Zhu, Mingjun Zhang, Tongxin Cheng, Haibing College of Information System Engineering PLA Strategic Support Force Information Engineering University Zhengzhou China National Key Laboratory of Science and Technology on Blind Signal Processing Chengdu China

ISBN: (纸本)9781510661325

Formation target track sorting is an important problem in multi-target track processing. Unlike the processing of periodic scans and point tracks of active radar, passive positioning data has the problems of irregular positioning period and difficulty in distinguishing multiple targets by target signal attributes. In this paper, we propose a track initiation algorithm for passive positioning system based on density clustering and Hough transform for the characteristics of passive positioning system. The algorithm first uses the density clustering algorithm to identify the cluster centers of targets with large measurement errors, and then uses the Hough transform method to initiate a track. © 2023 SPIE.

关键词： Hough transforms

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