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IET International Radar Conference (IET IRC 2020)

作者： X. Wang J. Gao L. Gao F. Wang Harbin Engineering University College of Information and Communication Engineering Harbin China Beijing Institute of Space Long March Vehicle National Key Laboratory of Science and Technology on Test Physics and Numerical Mathematics Beijing China

In order to improve the recognition rate of emitter signals modulation under low signal noise ratio (SNR), an end-to-end method based on the stacked denoising autoencoder (SDAE) - one dimensional convolutional neural network (ODCNN) is proposed in this paper. The SADE-ODCNN is designed in this method and trained through a two-step training. In the SDAE-ODCNN model, the encoder of the SDAE can extract the denoised and compressed features of the received emitter signals. Then the ODCNN can further extract features to realize the recognition. The simulation results show that the average recognition rate of the method can reach 0.94 under 0dB. Thus the proposed method has a good application in the field of emitter signals modulation recognition.

关键词： radar computing modulation feature extraction neural nets image denoising learning (artificial intelligence) image classification

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Advances in the Researches of the Middle and Upper Atmosphere in China in 2014-2016

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空间科学学报 2016年第5期36卷 738-752页

作者： CHEN Zeyu XU Jiyao HU Xiong CHEN Hongbin CHEN Wen WEI Ke BIAN Jianchun TIAN Wenshou ZHANG Shaodong REN Rongcai DOU Xiankang Key Laboratory of Middle Atmosphere and Global Environment Observation Institute of Atmospheric Physics Chinese Academy of Sciences Beijing 100029 National Space Science Center Chinese Academy of Sciences Beijing 100190 Institute of Atmospheric Physics Chinese Academy of Scienees Beijing 100029 School of Atmospheric Sciences Lanzhou University Lanzhou 730000 School of Electronic Information Wuhan University Wuhan 430072 State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics Institute of Atmospheric Physics Chinese Academy of Sciences Beijing 100029 School of Earth and Space Sciences University of Science and Technology of China Hefei 230026

In this report the research results by Chinese scientists in 2014—2016 are *** focuses are placed on the researches of the middle and upper atmosphere,specifically the researches associated with ground-based observation capabihty development,dynamical processes,and properties of circulation and chemistry-climate coupling of the middle atmospheric layers.

关键词：中高层大气中国科学家研究成果观察能力耦合特性大气化学中间层气候

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A Compound THz Meta-surface Absorber with Polarization Insensitivity and Angular Stability

A Compound THz Meta-surface Absorber with Polarization Insen...

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IEEE Asia-Pacific Conference on Antennas and Propagation (APCAP)

作者： Kai Wang Hailiang Zhu Ganyu Liu Jinchao Mou Pei Zheng Gao Wei Northwestern Polytechnical University School of Electronics and Information Xi'an Shaanxi CN Beijing Research Institute of Telemetry Beijing CN The National Key Laboratory of Science and Technology on Test Physics and Numerical Mathematics Beijing CN

In this paper, a wideband terahertz meta-surface absorber with ultra-thin thickness is proposed. The meta-surface unit cell is composed of four-square unit cells in two different sizes. The the absorption higher than 90% from 3.24 to 3.98THz is achieved which can be regarded as a perfect terahertz absorber. Due to the symmetrical layout of meta-surface unit cell, the absorption spectrum can be maintained for any linear polarized terahertz wave, and the absorptance can be kept higher than 80% while the incident angle increases before 45°. Furthermore, the thermal response is calculated to be 0.23 $\mathbf{K} \cdot{\mathbf{m}\mathbf{m}^{2}/ \upmu \mathbf{W}}$ that well suited the requirements of FPA detectors.

关键词： Sensitivity Absorption Layout Detectors Stability analysis Compounds Thermal stability

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A review of progress in coupled ocean-atmosphere model developments for ENSO studies in China

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Journal of Oceanology and Limnology 2020年第4期38卷 930-961页

作者： ZHANG Rong-Hua YU Yongqiang SONG Zhenya REN Hong-Li TANG Youmin QIAO Fangli WU Tongwen GAO Chuan HU Junya TIAN Feng ZHU Yuchao CHEN Lin LIU Hailong LIN Pengfei WU Fanghua WANG Lin Key Laboratory of Ocean Circulation and Waves Institute of Oceanologyand Center for Ocean Mega-ScienceChinese Academy of SciencesQingdao 266071China Laboratory for Ocean and Climate Dynamics Pilot National Laboratory for Marine Science and TechnologyQingdao 266237China Center for Excellence in Quaternary Science and Global Change Chinese Academy of SciencesXi’an 710061China University of Chinese Academy of Sciences Beijing 100049China LASG Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100049China First Institute of Oceanography Ministry of Natural ResourcesQingdao 266061China Laboratory for Regional Oceanography and Numerical Modeling Pilot National Laboratory for Marine Science and TechnologyQingdao 266237China Key Laboratory of Marine Science and Numerical Modeling(MASNUM) Ministry of Natural ResourcesQingdao 266061China National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology Qingdao 266061China State Key Laboratory of Severe Weather Chinese Academy of Meteorological SciencesBeijing 100081China Laboratory for Climate Studies and CMA-NJU Joint Laboratory for Climate Prediction Studies National Climate CenterChina Meteorological AdministrationBeijing 100081China Environmental Science and Engineering University of Northern British ColumbiaBritish Columbia V2N 4Z9Canada State Key Laboratory of Satellite Ocean Environment Dynamics Second Institute of OceanographyMinistry of Natural ResourcesHangzhou 310012China Key Laboratory of Meteorological Disaster Ministry of Education(KLME)and Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD)Nanjing University of Information Science and TechnologyNanjing 210044China Beijing Climate Center China Meteorological AdministrationBeijing 100081China

El Nino-Southern Oscillation(ENSO) is the strongest interannual signal that is producedby basinscale processes in the tropical Pacific,with significant effects on weather and climate *** the past,extensive and intensive international efforts have been devoted to coupled model developments for ENSO studies.A hierarchy of coupled ocean-atmo sphere models has been formulated;in terms of their complexity,they can be categorized into intermediate coupled models(ICMs),hybrid coupled models(HCMs),and fully coupled general circulation models(CGCMs).ENSO modeling has made significant progress over the past decades,reaching a stage where coupled models can now be used to successfully predict ENSO events 6 months to one year in ***,ENSO exhibits great diversity and complexity as observed in nature,which still cannot be adequately captured by current state-of-the-art coupled models,presenting a challenge to ENSO *** primarily reviewed the long-term efforts in ENSO modeling continually and steadily made at different institutions in China;some selected representative examples are presented here to review the current status of ENSO model developments and applications,which have been actively pursued with noticeable progress being made *** ENSO simulations are very sensitive to model formulations and process representations etc.,dedicated efforts have been devoted to ENSO model developments and ***,different ocean-atmosphere coupled models have been available in China,which exhibit good model performances and have already had a variety of applications to climate modeling,including the Coupled Model Intercomparison Project Phase 6(CMIP6).Nevertheless,large biases and uncertainties still exist in ENSO simulations and predictions,and there are clear rooms for their improvements,which are still an active area of researches and ***,model performances of ENSO simulations are assessed in terms of advantages and disadvantage

关键词： El Niño-Southern Oscillation(ENSO) coupled ocean-atmosphere models simulations and predictions model biases and uncertainties

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Digital Nonlinear Self-Interference Cancellation Using Sw-Gru-Tpa

SSRN

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SSRN 2024年

作者： Zhao, Zhongkai Xia, Shijie Gao, Lu Zheng, Pei Jiang, Yilin College of Information and Communication Engineering Harbin Engineering University Harbin150000 China National Key Laboratory of Science and Technology on Test Physics and Numerical Mathematic Beijing100876 China

In order to enhance spectrum utilization and decrease transmission delay, the 6G system adopts full-duplex(FD) mode. Simultaneous operation of the same frequency inevitably causes the receiver to receive the signal sent by the transmitter, leading to serious nonlinear self-interference due to the nonlinear distortion generated by the power amplifier(PA). This paper proposes hybrid layer structures SW-GRU-TPA for the implementation of digital self-interference cancellation(SIC), combined with Sliding Window (SW), Gated Recurrent Unit (GRU) , and Temporal Pattern Attention (TPA).The model can not only effectively utilize the influence of historical information on the signal, but also capture the spatial and temporal dependencies in the data to fit the nonlinear characteristics of the PA and the delay effect in multipath transmission. Meanwhile, by utilizing the L1 norm model pruning, the model parameters can be optimized, leading to improved processing efficiency, enhanced practicality, and increased convenience in real-world applications. Through the verification of the actual data, the performance of the SW-GRU-TPA network has improved by 7.95 dB, 7.79 dB, 3.45 dB and 3.13 dB respectively, compared to the RVTDNN, SW-GRU, HCRDNN and SW-GRU-AM *** the TPA is compressed by 42.17%, the ICR is only reduced by 1.58%. © 2024, The Authors. All rights reserved.

关键词： Power amplifiers

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Doffnet: A Distant Objects Rgb-T Semantic Segmentation Method Based on Cross-Level Interaction Fusion Network

SSRN

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SSRN 2024年

作者： Chen, Yu Li, Xiang Luan, Chao Hou, Weimin Liu, Haochen Xue, Lian Zhu, Zihui Zhang, Jianqi Liu, Delian Wu, Xin Wei, Linfang Jian, Chaochao Li, Jinze Academy of Military Sciences School of Physics and Optoelectronic Engineering Xidian University Xi’an710071 China Beijing Institute of Control & Electronics Technology Beijing100038 China National Key Laboratory of Science and Technology on Test Physics & Numerical Mathematics Beijing100076 China

RGB-T segmentation represents an innovative approach driven by advancements in multi-spectral detection, poised to replace traditional RGB segmentation methods. An effective cross-modality feature fusion module is essential for this technology;simultaneously, the precise segmentation of distant objects is likewise a significant challenge. Building on these two focuses, we propose an end-to-end distant object feature fusion network (DOFFNet) for RGB-T segmentation. Initially, we introduce a cross-level interaction fusion strategy (CLIF) and an inter-correlation fusion method (IFFM) in the encoder to enhance multi-scale feature expression and improve fusion accuracy. Subsequently, we propose a residual-dense pixel convolution (R-DPC) in the decoder with a trainable upsampling unit, which dynamically reconstructs information lost during encoding, particularly for distant objects whose features may vanish after pooling. Experimental results demonstrate that DOFFNet improves accuracy across five classes and effectively segments distant objects occupying 0.2-2% of total pixels, enhancing overall segmentation quality and detailed understanding of RGB-T scenes. © 2024, The Authors. All rights reserved.

关键词： Semantic Segmentation

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Impact of Perturbation Schemes on the Ensemble Prediction in a Coupled Lorenz Model

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Advances in Atmospheric sciences 2023年第3期40卷 501-513页

作者： Qian ZOU Quanjia ZHONG Jiangyu MAO Ruiqiang DING Deyu LU Jianping LI Xuan LI State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics(LASG) Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China College of Earth Science University of Chinese Academy of SciencesBeijing 100049China State Key Laboratory of Earth Surface Processes and Resource Ecology Beijing Normal UniversityBeijing 100875China Frontiers Science Center for Deep Ocean Multispheres and Earth System(FDOMES)/Key Laboratory of Physical Oceanography/Institute for Advanced Ocean Studies Ocean University of ChinaQingdao 266100China Laboratory for Ocean Dynamics and Climate Pilot Qingdao National Laboratory for Marine Science and TechnologyQingdao 266237China Department of Atmospheric and Oceanic Sciences and Institute of Atmospheric Sciences Fudan UniversityShanghai 200438China

Based on a simple coupled Lorenz model,we investigate how to assess a suitable initial perturbation scheme for ensemble forecasting in a multiscale system involving slow dynamics and fast *** initial perturbation approaches are used in the ensemble forecasting experiments:the random perturbation(RP),the bred vector(BV),the ensemble transform Kalman filter(ETKF),and the nonlinear local Lyapunov vector(NLLV)*** show that,regardless of the method used,the ensemble averages behave indistinguishably from the control forecasts during the first few time *** to different error growth in different time-scale systems,the ensemble averages perform better than the control forecast after very short lead times in a fast subsystem but after a relatively long period of time in a slow *** to the coupled dynamic processes,the addition of perturbations to fast variables or to slow variables can contribute to an improvement in the forecasting skill for fast variables and slow *** the initial perturbation approaches,the NLLVs show higher forecasting skill than the BVs or RPs *** NLLVs and ETKFs had nearly equivalent prediction skill,but NLLVs performed best by a narrow *** particular,when adding perturbations to slow variables,the independent perturbations(NLLVs and ETKFs)perform much better in ensemble *** results are simply implied in a real coupled air–sea *** the prediction of oceanic variables,using independent perturbations(NLLVs)and adding perturbations to oceanic variables are expected to result in better performance in the ensemble prediction.

关键词： ensemble prediction nonlinear local Lyapunov vector(NLLV) ensemble transform Kalman filter(ETKF) coupled air-sea models

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Cause of Extreme Heavy and Persistent Rainfall over Yangtze River in Summer 2020

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Advances in Atmospheric sciences 2021年第12期38卷 1994-2009页

作者： Xiao PAN Tim LI Ying SUN Zhiwei ZHU Key Laboratory of Meteorological Disaster Ministry of Education(KLME)/Joint International Research Laboratory of Climate and Environment Change(ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD)Nanjing University of Information Science and TechnologyNanjing 210044China International Pacific Research Center and Department of Atmospheric Sciences School of Ocean and Earth Science and TechnologyUniversity of Hawaii at ManoaHonoluluHawaii 96822USA National Climate Center Beijing 100081China State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China

Record-breaking heavy and persistent precipitation occurred over the Yangtze River Valley(YRV)in June-July(JJ)*** observational data analysis has indicated that the strong and persistent rainfall arose from the confluence of southerly wind anomalies to the south associated with an extremely strong anomalous anticyclone over the western North Pacific(WNPAC)and northeasterly anomalies to the north associated with a high-pressure anomaly over Northeast Asia.A further observational and modeling study has shown that the extremely strong WNPAC was caused by both La Niña-like SST anomaly(SSTA)forcing in the equatorial Pacific and warm SSTA forcing in the tropical Indian Ocean(IO).Different from conventional central Pacific(CP)El Niños that decay slowly,a CP El Niño in early 2020 decayed quickly and became a La Niña by early *** quick transition had a critical impact on the ***,an unusually large area of SST warming occurred in the tropical IO because a moderate interannual SSTA over the IO associated with the CP El Niño was superposed by an interdecadal/long-term trend *** sensitivity experiments have demonstrated that both the heating anomaly in the IO and the heating anomaly in the tropical Pacific contributed to the formation and maintenance of the *** persistent high-pressure anomaly in Northeast Asia was part of a stationary Rossby wave train in the midlatitudes,driven by combined heating anomalies over India,the tropical eastern Pacific,and the tropical Atlantic.

关键词： Yangtze River floods anomalous anticyclone over the western North Pacific CP and EP El Niño Indian Ocean warming La Niña Rossby wave train

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Meta or select?* : —history, argument and prospective about MTMs and FSS

Meta or select?* : —history, argument and prospective about...

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International Applied Computational Electromagnetics Society Symposium (ACES)

作者： Shengjun Zhang Mingliang Wang Xia Ai Yichun Cui Xin Liu Jiaqi Liu Gang Meng Zhaohui Qi Yuan Sun Yunhui Tang Hui Xue National Key Laboratory of Science & Technology on Test Physics and Numerical Mathematics Beijing China The Institute of Effectiveness Evaluation of Flying Vehicle Beijing China School of materials science and technology Beijing University of Technology Beijing China Beijing Institute of system engineering Beijing China

In this paper, the development history of metamaterials (MTMs) and Frequency selective surfaces (FSS) was sketched, and the two conception was discussed. Furthermore, state of the art of both terms was introduced and ... 详细信息

关键词： Frequency selective surfaces Metamaterials Lattices Crystals physics Electromagnetics Sun

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Influence of the NAO on Wintertime Surface Air Temperature over East Asia:Multidecadal Variability and Decadal Prediction

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Advances in Atmospheric sciences 2022年第4期39卷 625-642页

作者： Jianping LI Tiejun XIE Xinxin TANG Hao WANG Cheng SUN Juan FENG Fei ZHENG Ruiqiang DING Frontiers Science Center for Deep Ocean Multispheres and Earth System-Key Laboratory of Physical Oceanography-Institute for Advanced Ocean Studies-Academy of the Future Ocean Ocean University of ChinaQingdao 266100China Laboratory for Ocean Dynamics and Climate Pilot Qingdao National Laboratory for Marine Science and TechnologyQingdao 266237China College of Global Change and Earth System Sciences Beijing Normal UniversityBeijing 100875China State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China State Key Laboratory of Earth Surface Processes and Resource Ecology Beijing Normal UniversityBeijing 100875China

In this paper,we investigate the influence of the winter NAO on the multidecadal variability of winter East Asian surface air temperature(EASAT)and EASAT decadal *** observational analysis shows that the winter EASAT and East Asian minimum SAT(EAmSAT)display strong in-phase fluctuations and a significant 60-80-year multidecadal variability,apart from a long-term warming *** winter EASAT experienced a decreasing trend in the last two decades,which is consistent with the occurrence of extremely cold events in East Asia winters in recent *** winter NAO leads the detrended winter EASAT by 12-18 years with the greatest significant positive correlation at the lead time of 15 *** analysis shows that ENSO may affect winter EASAT interannual variability,but does not affect the robust lead relationship between the winter NAO and *** present the coupled oceanic-atmospheric bridge(COAB)mechanism of the NAO influences on winter EASAT multidecadal variability through its accumulated delayed effect of~15 years on the Atlantic Multidecadal Oscillation(AMO)and Africa-Asia multidecadal teleconnection(AAMT)*** NAO-based linear model for predicting winter decadal EASAT is constructed on the principle of the COAB mechanism,with good hindcast *** winter EASAT for 2020-34 is predicted to keep on fluctuating downward until~2025,implying a high probability of occurrence of extremely cold events in coming winters in East Asia,followed by a sudden turn towards sharp *** predicted 2020/21 winter EASAT is almost the same as the 2019/20 winter.

关键词： winter East Asian surface air temperature North Atlantic Oscillation Atlantic Multidecadal Oscillation Africa-Asia multidecadal teleconnection pattern coupled oceanic-atmospheric bridge multidecadal variability

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