Joint Representation and Recognition for Ship-Radiated Noise Based on Multimodal Deep Learning
Journal of Marine Science and Engineering, 2019 Ship recognition based on ship-radiated noise is one of the most important and challenging subjects in underwater acoustic signal processing. The recognition methods for ship-radiated noise recognition include traditional methods and deep learning (DL ...
Fei Yuan, Xiaoquan Ke, En Cheng
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Hierarchical Cosine Similarity Entropy for Feature Extraction of Ship-Radiated Noise [PDF]
Entropy, 2018 The classification performance of passive sonar can be improved by extracting the features of ship-radiated noise. Traditional feature extraction methods neglect the nonlinear features in ship-radiated noise, such as entropy.
Zhe Chen +3 more
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A New Ship-Radiated Noise Feature Extraction Technique Based on Variational Mode Decomposition and Fluctuation-Based Dispersion Entropy [PDF]
Entropy, 2019 Sea environment complexity and underwater acoustic channels make it hard to extract features of ship-radiated noise signals. This paper presents a novel feature extraction method using the advantages of variational mode decomposition (VMD), fluctuation ...
Hong Yang, Ke Zhao, Guohui Li
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Resonance-Based Time-Frequency Manifold for Feature Extraction of Ship-Radiated Noise [PDF]
Sensors, 2018 In this paper, a novel time-frequency signature using resonance-based sparse signal decomposition (RSSD), phase space reconstruction (PSR), time-frequency distribution (TFD) and manifold learning is proposed for feature extraction of ship-radiated noise,
Jiaquan Yan +4 more
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Feature Extraction of Ship-Radiated Noise Based on Regenerated Phase-Shifted Sinusoid-Assisted EMD, Mutual Information, and Differential Symbolic Entropy [PDF]
Entropy, 2019 To improve the recognition accuracy of ship-radiated noise, a feature extraction method based on regenerated phase-shifted sinusoid-assisted empirical mode decomposition (RPSEMD), mutual information (MI), and differential symbolic entropy (DSE) is ...
Guohui Li, Zhichao Yang, Hong Yang
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A Novel Denoising Method for Ship-Radiated Noise
Journal of Marine Science and Engineering, 2023 Ship-radiated noise (SN) is one of the most critical signals in the complex marine environment; however, it is inevitably contaminated by the marine environment’s noise as well as noise from other equipment.
Yuxing Li, Chunli Zhang, Yuhan Zhou
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Feature Extraction of Ship-Radiated Noise Based on Intrinsic Time-Scale Decomposition and a Statistical Complexity Measure [PDF]
Entropy, 2019 Extracting effective features from ship-radiated noise is an important way to improve the detection and recognition performance of passive sonar. Complexity features of ship-radiated noise have attracted increasing amounts of attention.
Junxiong Wang, Zhe Chen
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Using Feature Extraction to Perform Equipment Health Monitoring on Ship-Radiated Noise
Acoustics, 2023 The current state of the art in hydroacoustics research employs a variety of feature extraction techniques with the goal of accurately classifying a ship based on its radiated noise. These techniques are capable of accuracy in excess of 95%.
Nicholas Marasco +2 more
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QiandaoEar22: a high-quality noise dataset for identifying specific ship from multiple underwater acoustic targets using ship-radiated noise [PDF]
EURASIP Journal on Advances in Signal ProcessingTarget identification of ship-radiated noise is a crucial area in underwater target recognition. However, there is currently a lack of multi-target ship datasets that accurately represent real-world underwater acoustic conditions.
Xiaoyang Du, Feng Hong
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Ship-Radiated Noise Separation in Underwater Acoustic Environments Using a Deep Time-Domain Network
Journal of Marine Science and EngineeringShip-radiated noise separation is critical in both military and economic domains. However, due to the complex underwater environments with multiple noise sources and reverberation, separating ship-radiated noise poses a significant challenge ...
Qunyi He +3 more
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