Results 31 to 40 of about 22,986 (292)
LPI Radar Waveform Recognition Based on Deep Convolutional Neural Network Transfer Learning [PDF]
, 2019 Low Probability of Intercept (LPI) radar waveform recognition is not only an important branch of the electronic reconnaissance field, but also an important means to obtain non-cooperative radar information.
Guoqing Ruan, Xin Yu, Qiang Guo
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LPI Radar Waveform Recognition Based on Multi-Resolution Deep Feature Fusion
IEEE Access, 2021 Deep neural networks are used as effective methods for the Low Probability of Intercept (LPI) radar waveform recognition. However, existing models' performance degrades seriously at low Signal-to-Noise Ratios (SNRs) because the effective features ...
Xue Ni +4 more
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Texture recognition based on magnetostrictive tactile sensor array and convolutional neural network
AIP Advances, 2023 Tactile sensors are key devices in surface information perception for robots that can recognize the surface texture of fabrics with different materials and winding patterns in unstructured environments, thus helping the robot process fabrics more ...
Zhuolin Li +4 more
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LPI Radar Waveform Recognition Based on CNN and TPOT [PDF]
, 2019 The electronic reconnaissance system is the operational guarantee and premise of electronic warfare. It is an important tool for intercepting radar signals and providing intelligence support for sensing the battlefield situation.
Jian Wan, Xin Yu, Qiang Guo
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Understanding and Ameliorating Non-Linear Phase and Amplitude Responses in AMCW Lidar [PDF]
, 2011 Amplitude modulated continuous wave (AMCW) lidar systems commonly suffer from non-linear phase and amplitude responses due to a number of known factors such as aliasing and multipath inteference. In order to produce useful range and intensity information
Michael J. Cree +5 more
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EURASIP Journal on Wireless Communications and Networking, 2007 Automatic target recognition (ATR) in target search phase is very challenging because the target range and mobility are not yet perfectly known, which results in delay-Doppler uncertainty.
Qilian Liang
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Automatic LPI Radar Waveform Recognition Using CNN
IEEE Access, 2018 Detecting and classifying the modulation scheme of the intercepted noisy low probability of intercept (LPI) radar signals in real time is a necessary survival technique required in the electronic warfare systems. Therefore, LPI radar waveform recognition
Seung-Hyun Kong +3 more
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Speech recognition of mandarin monosyllables [PDF]
, 2014 The nonlinear dynamic characteristics of expansion and contraction and the sequential time-varying features of the syllable pronunciations greatly complicate the tasks of automatic speech recognition. Each syllable is represented by a sequence of vectors
Li, T.F.
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An FPGA-Based Time-Domain Waveform Recognition Method Using Multi-Feature Voting Fusion
Applied SciencesIdentifying the time-domain waveform type under broadband conditions is a basic but very challenging task. Traditional methods based on frequency domain or training models generally have the problems of high resource consumption, large delay, and ...
Yiqi Tang, Zheng Li, Lin Zheng
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Data-Driven Approach for Electromagnetic Transient Recognition Using Transfer Learning
CSEE Journal of Power and Energy SystemsRecognition methods of electromagnetic transients (EMT) have been widely used in power systems with the assumption that training and testing data are drawn from the same probability distribution.
Han Zhang, Wenxia Sima, Ming Yang
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