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arXiv 2024年

作者： Wan, Xujie Li, Wenjie Gao, Guangwei Lu, Huimin Yang, Jian Lin, Chia-Wen The Institute of Advanced Technology Nanjing University of Posts and Telecommunications Nanjing210046 China Key Laboratory of Artificial Intelligence Ministry of Education Shanghai200240 China The Provincial Key Laboratory for Computer Information Processing Technology Soochow University Suzhou215006 China The Pattern Recognition and Intelligent System Laboratory School of Artificial Intelligence Beijing University of Posts and Telecommunications Beijing100080 China The School of Automation Southeast University Nanjing210096 China The School of Computer Science and Technology Nanjing University of Science and Technology Nanjing210094 China The Department of Electrical Engineering National Tsing Hua University Hsinchu30013 Taiwan

Recently, CNN and Transformer hybrid networks demonstrated excellent performance in face super-resolution (FSR) tasks. Since numerous features at different scales in hybrid networks, how to fuse these multi-scale features and promote their complementarity is crucial for enhancing FSR. However, existing hybrid network-based FSR methods ignore this, only simply combining the Transformer and CNN. To address this issue, we propose an attention-guided Multi-scale interaction network (AMINet), which contains local and global feature interactions as well as encoder-decoder phases feature interactions. Specifically, we propose a Local and Global Feature Interaction Module (LGFI) to promote fusions of global features and different receptive fields' local features extracted by our Residual Depth Feature Extraction Module (RDFE). Additionally, we propose a Selective Kernel Attention Fusion Module (SKAF) to adaptively select fusions of different features within LGFI and encoder-decoder phases. Our above design allows the free flow of multi-scale features from within modules and between encoder and decoder, which can promote the complementarity of different scale features to enhance FSR. Comprehensive experiments confirm that our method consistently performs well with less computational consumption and faster inference. Copyright © 2024, The Authors. All rights reserved.

关键词： Decoding

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Monaural Speech Enhancement Using a Multi-Branch Temporal Convolutional Network

SSRN

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SSRN 2022年

作者： Zhang, Qiquan Qian, Xinyuan Nicolson, Aaron Wang, Chenxu Paliwal, Kuldip K. Department of Electrical and Computer Engineering National University of Singapore Singapore Australian e-Health Research Centre CSIRO Australia School of Information and Electrical Engineering Harbin Institute of Technology Weihai264209 China Signal Processing Laboratory Griffith University BrisbaneQLD4160 Australia

Deep learning has achieved substantial improvement on single-channel speech enhancement. The performance of multi-layer perceptrons (MLPs)-based methods is limited by the ability to capture the long-term contextual information. The recurrent neural networks (RNNs), e.g., long short-term memory (LSTM) model, are able to capture the long-term temporal dependencies, but suffer from the high latency and the complex training process. Recently, temporal convolution networks (TCNs), employing 1-D dilated convolution and residual learning, achieves gained considerable success in speech enhancement. In this paper we propose a novel TCN model that employs multi-branch structure, called multi-branch TCN (MB-TCN), for monaural speech enhancement. The MB-TCN exploits split-transform-aggregate design, which is expected to obtain strong representational power with higher parameter efficiency. The MB-TCN model applies 1-D causal dilated CNN in each branch to expand receptive fields for capturing long-term temporal contextual information. Our extensive experimental investigation suggests that MB-TCNs outperform the residual LSTMs (ResLSTMs), TCNs, and the CNNs with dense aggregations (DenseNet) in terms of speech intelligibility and quality, while providing superior parameter efficiency. Furthermore, our proposed MB-TCN model demonstrates highly competitive performance to multiple state-of-the-art speech enhancement methods in terms of five widely used objective metrics. © 2022, The Authors. All rights reserved.

关键词： Convolution

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Magnetospheric control of ionospheric TEC perturbations via whistler-mode and ULF waves

arXiv

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arXiv 2024年

作者： Shen, Yangyang Verkhoglyadova, Olga P. Artemyev, Anton Hartinger, Michael D. Angelopoulos, Vassilis Shi, Xueling Zou, Ying Department of Earth Planetary and Space Sciences University of California Los AngelesCA United States Jet Propulsion Laboratory California Institute of Technology PasadenaCA United States Space Science Institute Center for Space Plasma Physics BoulderCO United States Department of Electrical and Computer Engineering Virginia Tech BlacksburgVA United States Johns Hopkins University Applied Physics Laboratory LaurelMD United States

The weakly ionized plasma in the Earth's ionosphere is controlled by a complex interplay between solar and magnetospheric inputs from above, atmospheric processes from below, and plasma electrodynamics from within. This interaction results in ionosphere structuring and variability that pose major challenges for accurate ionosphere prediction for global navigation satellite system (GNSS) related applications and space weather research. The ionospheric structuring and variability are often probed using the total electron content (TEC) and its relative perturbations (dTEC). Among dTEC variations observed at high latitudes, a unique modulation pattern has been linked to magnetospheric ultra low frequency (ULF) waves, yet its underlying mechanisms remain unclear. Here using magnetically-conjugate observations from the THEMIS spacecraft and a groundbased GPS receiver at Fairbanks, Alaska, we provide direct evidence that these dTEC modulations are driven by magnetospheric electron precipitation induced by ULF-modulated whistler-mode waves. We observed peak-to-peak dTEC amplitudes reaching ∼0.5 TECU (1 TECU is equal to 106electrons/m2) with modulations spanning scales of ∼5-100 km. The cross-correlation between our modeled and observed dTEC reached ∼0.8 during the conjugacy period but decreased outside of it. The spectra of whistler-mode waves and dTEC also matched closely at ULF frequencies during the conjugacy period but diverged outside of it. Our findings elucidate the high-latitude dTEC generation from magnetospheric wave-induced precipitation, addressing a significant gap in current physics-based dTEC modeling. Theses results thus improve ionospheric dTEC prediction and enhance our understanding of magnetosphere-ionosphere coupling via ULF waves. © 2024, CC BY.

关键词： Ionosphere

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Structural inversion asymmetry in epitaxial ultrathin films of Bi(111)/InSb(111)B

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Physical Review Materials 2025年第5期9卷 054202-054202页

作者： Hadass S. Inbar Muhammad Zubair Jason T. Dong Aaron N. Engel Connor P. Dempsey Yu Hao Chang Shinichi Nishihaya Shoaib Khalid Alexei V. Fedorov Anderson Janotti Chris J. Palmstrøm Materials Department UC Santa Barbara California 93106 USA Department of Physics and Astronomy University of Delaware Newark Delaware 19716 USA Department of Materials Science and Engineering University of Delaware Newark Delaware 19716 USA Department of Electrical & Computer Engineering UC Santa Barbara California 93106 USA Present address: Department of Physics Tokyo Institute of Technology Tokyo 152-8551 Japan. Princeton Plasma Physics Laboratory Princeton New Jersey 08540 USA Advanced Light Source Lawrence Berkeley National Laboratory Berkeley California 94720 USA

Bismuth (Bi) films hold potential for spintronic devices due to strong spin-orbit coupling. Understanding the growth, surface states, and interactions with the substrate is key to their functionalization. Large-area high-quality (111) Bi ultrathin films were grown on InSb (111)B substrates by molecular beam epitaxy (MBE). Strong film-substrate interactions epitaxially stabilize the (111) orientation and lead to nonequivalent interface potentials. Analysis of angle-resolved photoemission spectroscopy (ARPES) measurements, employed to characterize the evolution of the surface states with film thickness, indicate a crossing at the M¯ point, suggesting a topologically trivial phase in the thin film. The results show the presence of interfacial bonds to the substrate breaks inversion symmetry, preventing the semimetal-to-semiconductor transition predicted for freestanding bismuth layers, highlighting the importance of controlled functionalization and surface passivation of two-dimensional materials.

关键词： Ultrathin films

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Dielectric strength characterization in BSZT ceramic capacitors

Dielectric strength characterization in BSZT ceramic capacit...

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International Conference on Pulsed Power

作者： Lauro P. Silva Neto Rangel G. Aredes José O. Rossi Eduardo Antonelli Gustavo N. Lima Edl. Schamiloglu Joaquim J. Barroso Dept.Science and Technology Federal University of São Paulo São José dos Campos Brazil Associated Plasma Laboratory National Institute for Space Research São José dos Campos Brazil Electrical and Computer Engineering Department University of New Mexico Albuquerque USA

Ceramic capacitors are used in electronic devices that need a specific behavior or some project requirements such as temperature range, maximum voltage, dielectric strength, low loss, and others. In this work we synthesized ceramic capacitors using BSZT (Barium, Strontium, Zirconium, and Titanium) to be applied in Nonlinear Transmission Lines - NLTLs to produce high-power oscillations. In addition to sintering, we performed a dielectric strength characterization using ten samples and the Weibull distribution to determine the average dielectric strength and standard deviation. The results showed a ceramic material with dielectric strength of the order of 7.0 kV/mm and a standard deviation of +/- 1.2 kV/mm.

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A Retina-LGN-V1 Structure-like Spiking Neuron Network for Image Feature Extraction 21

A Retina-LGN-V1 Structure-like Spiking Neuron Network for Im...

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Proceedings of the 2021 5th International Conference on Video and Image processing

作者： Sheng Ji Qijun Gu Ye Yuan Peng Zhao Tao Fang Hong Huo Xin Niu Department of Automation_School of Electronic Information and Electrical Engineering_Key Laboratory of System Control and Information Processing Ministry of Education Shanghai Jiao Tong University China College of Computer Science and Technology on Parallel and Distributed Laboratory National University of Defense Technology China

ISBN: (纸本)9781450385893

SNNs have achieved great attention in recent years as they contain neurons more like those in the brain and use spikes to encode and transmit information efficiently among neurons with lower energy consumption. A Retina-LGN-V1 structure-like spiking neuron network (RLVSL-SNN) is proposed in this paper. It is inspired by the structure of mammalian primary visual pathway, and simulates different biological structures of Retina, LGN and V1. Noise reduction circuit and light adaptation circuit are also simulated for enhancing the robustness of its extracted features. RLVSL-SNN is a bio-plausible neuron network as it has firing rates of neurons in each layer that are similar to those of biological experiments. Besides, a full-connected SNN (FC SNN) is implemented following RLVSL-SNN for classification to evaluate the extracted features. The additive spiking timing dependent plasticity (STDP) learning rules and the ANN-to-SNN conversion method are utilized to train RLVSL-SNN and FC SNN, respectively. The experiments on MNIST dataset have verified that RLVSL-SNN is comparable to AlexNet for classification by features from spikes.

关键词： Additive Spiking Timing Dependent Plasticity Learning Primary Visual Pathway Image Classification Spiking Neural Network

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STAR-RIS Enhanced Covert Communication with Delay Constraint

STAR-RIS Enhanced Covert Communication with Delay Constraint

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IEEE International Conference on Communications in China (ICCC)

作者： Beixi Cheng Jinsong Hu Youjia Chen Feng Shu Zhizhang David Chen College of Physics and Information Engineering Fuzhou University Fuzhou Fujian Fujian Key Laboratory for Intelligent Processing and Wireless Transmission of Media Information Fuzhou China School of Electronic and Optical Engineering Nanjing University of Science and Technology Nanjing China School of Information and Communication Engineering Hainan University Haikou China Department of Electrical and Computer Engineering Dalhousie University Halifax NS Canada

This work confirms the performance gain achieved by deploying a simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) in covert communication. To maximize the system covert rate, we jointly optimize the power allocation coefficients at the transmitter and the transmission and reflection coefficients at the STAR-RIS, subject to the delay-constrained and power-constrained. Furthermore, we propose a two-stage alternating optimization algorithm based on the semidefinite relaxation (SDR) method to derive the optimal solutions to the above non-convex optimization problem. The effectiveness and superiority of the proposed algorithm and STAR-RIS-assisted covert scheme are demonstrated by the numerical results.

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Efficient Gridless DoA Estimation Method of Non-uniform Linear Arrays with Applications in Automotive Radars

arXiv

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arXiv 2023年

作者： Gao, Silin Zhang, Zhe Wang, Muhan Zhang, Yan Zhao, Jie Zhang, Bingchen Wang, Yue Wu, Yirong Aerospace Information Research Institute Chinese Academy of Sciences Beijing China Key Laboratory of Technology in Geo-spatial Information Processing and Application System Chinese Academy of Sciences Beijing China School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing China Suzhou Key Laboratory of Microwave Imaging Processing and Application Technology Suzhou Aerospace Information Research Institute Jiangsu Suzhou China The Beijing Autoroad Tech Co. Ltd China Electrical and Computer Engineering Department George Mason University FairfaxVA United States

This paper focuses on the gridless direction-of-arrival (DoA) estimation for data acquired by non-uniform linear arrays (NLAs) in automotive applications. Atomic norm minimization (ANM) is a promising gridless sparse recovery algorithm under the Toeplitz model and solved by convex relaxation, thus it is only applicable to uniform linear arrays (ULAs) with array manifolds having a Vandermonde structure. In automotive applications, it is essential to apply the gridless DoA estimation to NLAs with arbitrary geometry with efficiency. In this paper, a fast ANM-based gridless DoA estimation algorithm for NLAs is proposed, which employs the array manifold separation technique and the accelerated proximal gradient (APG) technique, making it applicable to NLAs without losing of efficiency. Simulation and measurement experiments on automotive multiple-input multiple-outpt (MIMO) radars demonstrate the superiority of the proposed method. Copyright © 2023, The Authors. All rights reserved.

关键词： Efficiency

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Automatic Modulation Classification of Frequency-Hopping Signals Using High-Dimensional Phase Diagrams

Automatic Modulation Classification of Frequency-Hopping Sig...

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2023 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting, BMSB 2023

作者： Chen, Qibo Yan, Kun Wu, Hsiao-Chun Chang, Shih Yu Yan, Xiao Wu, Yiyan Chang, Haonan Guilin University of Electronic Technology Guangxi Key Laboratory of Wireless Wideband Communication and Signal Processing GuilinGuangxi China Guilin University of Electronic Technology Department of Information and Telecommunication Guangxi Guilin541004 China Louisiana State University School of Electrical Engineering and Computer Science Baton RougeLA70803 United States San Jose State University Department of Applied Data Science San JoseCA95192 United States University of Electronic Science and Technology of China School of Aeronautics and Astronautics Chengdu China Communications Research Centre Canada OttawaK2H 8S2 Canada Haonan Chang Is with Xi'an University Xi'an China

ISBN: (纸本)9798350321524

Automatic modulation recognition for frequency-hopping (FH) signals remains very challenging to researchers due to the signals' time-varying spectral characteristics. In this work, a novel robust automatic modulation recognition scheme is investigated for FH signals using the phase-space topological features represented by the embedded phase diagrams. As such embedded phase diagrams are often high-dimensional, it is necessary to formulate the phase-space features as tensors. In the training process, the phase-space tensor features will be utilized to establish the regression models as linear encoders for the individual modulations. The aforementioned linear encoders are constructed using the support vector machine (SVM);the phase-space feature-tensors of the training signals of all modulations will be projected by their corresponding regression models (or linearly encoded) to produce the representative code-vectors, respectively. In the test stage, the phase-space feature-tensor produced from a test signal will be projected by each individual trained regression model (or linearly encoded) to generate the respective code-vectors. Then, the code-vectors resulting from the test stage will be compared with the representative code-vectors to find which modulation will lead to the smallest Euclidean distance in between and such a modulation will be picked as the modulation type of the test signal. Monte Carlo simulation results have demonstrated that the average recognition accuracy of our proposed new approach is more than 90% when the signal-to-noise ratio is no less than 0 dB for additive white Gaussian noise. © 2023 IEEE.

关键词： Support vector machines

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Time-Domain Traveling Wave Model of Single-Section Quantum Dot Mode-Locked Lasers with Optical Feedback

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Journal of Harbin Institute of technology(New Series) 2021年第3期28卷 45-52页

作者： Xuefang Xiao Zewang Zhang Xiupu Zhang School of Opto-electronic and Communication Engineering Xiamen University of TechnologyXiamen 361024FujianChina Key Laboratory of Communication Network and Information Processing in Fujian Province Xiamen 361024FujianChina Photonics Labs. Department of Electrical and Computer EngineeringConcordia UniversityMontreal QC H3G 1M8Canada

The optical feedback modulations of a passively mode-locked semiconductor laser with quantum dot structure were investigated in this study. The delay-induced dynamics of QD MLL under the condition of optical feedback have been studied by exploiting a time domain traveling wave(TDTW) model. The conventional TDTW model was improved to make it suitable for studying optical feedback system, especially the system with long external cavity structure. Combing the TDTW model with optical feedback and carrier rate equations, the pulse variation of a single section QD MLL was studied. This new model shows good agreement with the published experimental data. The roundtrip time and local light intensity modulation to the pulse evolution of QD MLL were studied. The results show that when the time for a light to go to and return from external cavity is equal to the integral times of the period of laser pulse without external feedback, resonance will be formed, and the period of pulse sequence is the shortest. The results also show that the stronger the local light intensity modulation is, the shorter the pulse period is.

关键词： quantum dot structure passively mode-locked laser optical feedback

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