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5th IEEE International Conference on Electronics technology, ICET 2022

作者： Lu, Shihang Su, Zhengyu Liao, Kaisheng Li, Chao Xiao, Zhuoling Yan, Bo Lin, Shuisheng Wu, Bo University of Electronic Science and Technology of China Science and Technology on Electronic Information Control Laboratory National Key Laboratory of Science and Technology on Blind Signal Processing School of Information and Communication Engineering China

ISBN: (纸本)9781665485081

Receiver plays a vital role in various electronic countermeasure systems and has always been a hot topic to research. Based on the traditional receiver digital channelization structure, this paper further researches and derives the high-efficiency digital channelization structure based on polyphase discrete Fourier transform corresponding to various application scenarios. Then we design a 256-sub-channel digital channelization system and implement it on a 64-channel parallel digital down converter to verify the structure. The system design relies on system on chip as the platform, and we verify the feasibility of it on field programmable gate array. © 2022 IEEE.

关键词： System-on-chip

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A Symbol Rate Estimation Scheme for Non-Cooperative Communication 7

A Symbol Rate Estimation Scheme for Non-Cooperative Communic...

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7th International Conference on Computer and Communications, ICCC 2021

作者： Lu, Jian Xu, Wenbo Wang, Siye Qi, Huiying Li, Yabin Beijing University of Posts and Telecommunications Key Laboratory of Universal Wireless Communications Beijing China National Key Laboratory of Science and Technology On Blind Signal Processing Shanghai China

ISBN: (纸本)9781665409506

In non-cooperative communication, symbol rate estimation is a prerequisite for signal demodulation. However, it is particularly difficult to estimate the symbol rate in the scenario with unknown modulation type and root cosine roll-off shaping. In this paper, an estimator without the requirement of communication parameters is proposed. First, the signal is recognized as constant envelope or non-constant envelope signal by square spectrum. Then, for the former, the symbol rate estimation is based on wavelet transform;for the latter, an envelope velocity strategy is adopted. In the proposed scheme, we elaborate some design details, including resampling factor, extraction of discrete spectral lines in the squared spectrum, selection of wavelet transform scale, and compensation of frequency deviation. We further propose a low-complexity implementation to meet the requirements for real-time capability and accuracy. Simulation results show that our proposed scheme is effective and accurate. © 2021 IEEE.

关键词： Wavelet transforms

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Active learning for spam email classification 2

Active learning for spam email classification

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2nd International Conference on Algorithms, Computing and Artificial Intelligence, ACAI 2019

作者： Chen, Zheng Tao, Ruiwen Wu, Xiaoyang Wei, Zhimin Luo, Xiao School of Information and Software Engineering University of Electronic Science and Technology of China China National Key Laboratory of Science and Technology on Blind Signal Processing Chengdu Sichuan China

ISBN: (纸本)9781450372619

Deep learning has yielded state-of-the-art performance on text classification tasks. In this paper, a new neural network based on Long-Short-Term-Memory model is applied to classify spam emails. Using deep learning method to classify spam emails requires large amounts of labeled data. To solve this problem, active learning method is used to reduce labeling cost and increase model adaptability. In this paper, it is found that the new model performs better than standard CNNs and RNNs on email classification task, and active learning methods can match state-of-the-art performance with just 10% of the labeled data. © 2019 ACM.

关键词： Long short-term memory

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Radio Frequency Fingerprint Extraction of Radio Emitter Based on I/Q Imbalance

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Procedia Computer science 2017年 107卷 472-477页

作者： Fei zhuo Yuanling Huang Jian chen National Key Laboratory of Science and Technology on Blind Signal Processing Chengdu China

Specific emitter identification use external signal feature called radio frequency fingerprint to identify the different radio transmitter, which does not rely on information content. A radio frequency fingerprint feature extraction approach based on I/Q imbalance of quadrature modulation signal is proposed. A I/Q modulator model is utilized to investigate the sources of radio frequency fingerprint and the effect on signal. A fingerprint features extraction based on signal space is proposed, but the SNR (signal to Noise Ratio) need to be estimated before. Simulation results demonstrate that the method have superior performance than previous bispectrum-based, Hibert-Huang transform-based approaches.

关键词： specific emitter identification I/Q imbalance signal space autocorrelation matrix

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Deep Graph Learning on Bipartite Observed Networks 2

Deep Graph Learning on Bipartite Observed Networks

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2nd Asia-Pacific Conference on Communications technology and Computer science, ACCTCS 2022

作者： Wei, Qiang School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu China National Key Laboratory of Science and Technology on Blind Signal Processing Chengdu China

ISBN: (纸本)9781665400343

In real-world settings, network structure observations are often incomplete due to the difficulties of data collection. However, most existing network analysis methods assume that the whole underlying structure is observed. In this paper, we focus on a common but overlooked network observation, named bipartite observation. We systematically study the influence of bipartite observations, and give an analytical representation using the stochastic block model. Moreover, we propose a new framework LP-GNN, which combines link prediction, sparsification, and graph neural networks for node classification tasks in bipartite observations. The effectiveness of LP-GNN is illustrated by experimental results on real datasets. © 2022 IEEE.

关键词： Graph neural networks

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Cramer-Rao Bound of TDOA estimation for frequency-hopping signals in fading channels

Cramer-Rao Bound of TDOA estimation for frequency-hopping si...

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IEEE China Summit and International Conference on signal and Information processing, ChinaSIP 2015

作者： Xinxin, Ouyang Qun, Wan Jinyu, Xiong Fei, Wen Department of Electronic Engineering University of Electronic Science and Technology of China Chengdu611731 China National Key Laboratory of Science and Technology on Blind Signal Processing Chengdu 610041 China

ISBN: (纸本)9781479919482

This paper presents the Cramer-Rao Bound (CRB) of time-difference-of-Arrival (TDOA) estimation for frequency-hopping (FH) signals, which has still not been reported in the open literature. The CRBs are derived in closed-form for both flat fading and frequency-selective channel models. The derived bounds provide insights into the influence of the FH parameters of a FH signal on TDOA estimate accuracy over flat fading and frequency-selective channels. Simulation results are provided to verify the theoretical findings. © 2015 IEEE.

关键词： Cramer-Rao bounds

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An Information Quantity-Based Uncertainty Measure to Incomplete Numerical Systems 1

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9th International Conference on Fuzzy Information and Engineering, ICFIE 2017

作者： Guo, Xin Xiang, Yingzhuo Shu, Lan School of Mathematical Sciences University of Electronic Science and Technology of China Chengdu611731 China National Key Laboratory of Science and Technology on Blind Signal Processing Chengdu610041 China

ISBN: (数字)9783030027773

ISBN: (纸本)9783030027766

The uncertainty measure plays an important role in the analysis of data. At present, many uncertain measures for incomplete information systems or incomplete decision systems have been developed. However, these measures are mainly aimed at discrete valued information systems, but they are not suitable for real valued data sets. In this paper, we mainly study the uncertainty measurement method of incomplete numerical information systems. By introducing neighborhood tolerant rough sets model, each concept has a neighborhood tolerant subset called neighborhood tolerance granule. Neighborhood tolerance information quantity uncertainty measure is proposed. We then prove that it satisfies non-negativity and monotonicity, giving maximum and minimum values. On this basis, the concept of neighborhood-tolerance joint quantity and neighborhood-tolerance condition quantity is proposed, and the relation between them and neighborhood tolerance information is discussed. Theoretical analysis and experimental results show that, in incomplete numerical information systems, the uncertainty measures we propose are performed better than the neighborhood-tolerance approximation accuracy measure in some case. © 2019, Springer Nature Switzerland AG.

关键词： Information systems

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A signal Synchronization and Pilot-Aided DOA Estimation Method in the presence of Interferences 6

A Signal Synchronization and Pilot-Aided DOA Estimation Meth...

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6th IEEE International Conference on Computer and Communications, ICCC 2020

作者： Wei, Lanxin Wang, Siye Xu, Wenbo Li, Dong Yang, Kun Network and Wireless Communication Lab Beijing University of Posts and Telecommunications Beijing China National Key Laboratory of Science and Technology on Blind Signal Processing Shanghai China

ISBN: (纸本)9781728186351

Direction of arrival (DOA) estimation is a fundamental problem in signal processing. The super-resolution spatial spectrum estimation algorithm based on feature decomposition, such as multiple signal classification (MUSIC) and estimating signal parameter via rotational invariance techniques (ESPRIT), has a good performance in high signal-to-interference plus noise ratio (SINR) environment and single interference. However, strong interferences will make DOA estimation error. And the number of angles that can be estimated by these methods is limited by the freedom of the antenna. The existence of multiple interferences will affect accuracy of DOA estimation. To address this problem, in this paper, we propose a novel dual-channel synchronization architecture and a Piloted-Aided DOA estimation method. We improve the matching performance by dual channel synchronization. A new matched filter is designed by using the idea of filter truncation, which reduces the computational resource cost. And a new DOA estimation method is proposed, which can estimate the angle of target signal in the environment of low SINR and multiple interferences. Experiments were performed to verify the performance of the proposed design. Results show that this architecture can greatly reduce the computational complexity. And the method successfully gets the direction of target signal in low SINR environment. © 2020 IEEE.

关键词： Synchronization

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Network completion via deep metric learning

Network completion via deep metric learning

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2020 International Conference on Big Data Mining and Information processing, BDMIP 2020

作者： Wei, Qiang School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu611731 China National Key Laboratory of Science and Technology on Blind Signal Processing Chengdu610041 China

Completing networks is often a necessary step when dealing with problems arising from applications in incomplete network data mining. This paper investigates the network completion problem with node attributes. We proposed a new method called DeepMetricNC by exploiting the correlation between node attributes and the underlying network structure. In DeepMetricNC, the correlation is modeled as a nonlinear mapping from node attributes to the probability of edge existence. To obtain the mapping, deep metric learning is applied with batch training and random negative sampling. DeepMetricNC has linear training time complexity and can adapt to large-scale network completion tasks. Experiments of real networks show that DeepMetricNC completes network structures better than other methods, and is more suitable when the portion of the observed part is small. © Published under licence by IOP Publishing Ltd.

关键词： Mapping

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Cooperative Optimization Method of UAV Swarm for Multi-objective High-Precision Location 5th

Cooperative Optimization Method of UAV Swarm for Multi-objec...

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5th Chinese Conference on Swarm Intelligence and Cooperative Control, CCSICC 2021

作者： Li, Bowen Ji, Xiaoting Huang, Yuanling School of Information System Engineering Information Engineering University Zhengzhou450001 China National Key Laboratory of Science and Technology on Blind Signal Processing Chengdu610041 China

ISBN: (纸本)9789811939976

In the field of electromagnetic radiation source location, using UAVs to locate the radiation source target has become a new location method. At present, the UAV swarm cooperative optimization method for high-precision location has some challenges, such as insufficient ability of multi-objective high-precision location, poor timeliness and so on. To solve these problems, this paper proposes a cooperative optimization method of UAV swarm for multi-objective location. Firstly, the multi-objective joint location accuracy is derived, which is taken as the objective function of swarm cooperative optimization. Secondly, in order to allocate multiple UAVs to multiple targets efficiently, the initialization strategy based on target isolation and the random allocation method of UAV based on probability are proposed. Finally, by combining the above improved strategies, an optimization method of UAV swarm cooperative location is proposed. Through the analysis of experimental results, the cooperative optimization method in this paper has obvious advantages in global optimization and convergence ability, which can improve the joint location accuracy and optimization speed. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Unmanned aerial vehicles (UAV)

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