首页|期刊导航|防务技术|MmPiFNN:A multi-mode physics-informed fuzzy neural network for passive recognition of surface ships by underwater equipment using ship radiated noise signals

MmPiFNN:A multi-mode physics-informed fuzzy neural network for passive recognition of surface ships by underwater equipment using ship radiated noise signalsOA

MmPiFNN:A multi-mode physics-informed fuzzy neural network for passive recognition of surface ships by underwater equipment using ship radiated noise signals

Feng Liu;Zipeng Li;Kunde Yang;Fuhu Chen;Junru Yu

School of Marine Science and Technology,Northwestern Polytechnical University,Xi'an,710072,China||Hanjiang National Laboratory,Wuhan,430060,China||Key Laboratory of Ocean Acoustics and Sensing(Northwestern Polytechnical University),Ministry of Industry and Information Technology,Xi'an,710072,ChinaOcean Institute of Northwestern Polytechnical University,Taicang,215400,China||School of Marine Science and Technology,Northwestern Polytechnical University,Xi'an,710072,China||Key Laboratory of Ocean Acoustics and Sensing(Northwestern Polytechnical University),Ministry of Industry and Information Technology,Xi'an,710072,ChinaOcean Institute of Northwestern Polytechnical University,Taicang,215400,China||School of Marine Science and Technology,Northwestern Polytechnical University,Xi'an,710072,China||Key Laboratory of Ocean Acoustics and Sensing(Northwestern Polytechnical University),Ministry of Industry and Information Technology,Xi'an,710072,ChinaHanjiang National Laboratory,Wuhan,430060,ChinaSchool of Marine Science and Technology,Northwestern Polytechnical University,Xi'an,710072,China

Ship radiated noisePhysical constraintMode fusionFuzzy systemPassive recognition

Ship radiated noisePhysical constraintMode fusionFuzzy systemPassive recognition

《防务技术》 2026 (5)

243-266,24

This work was supported by the Joint Training Fund Project of Hanjiang National Laboratory(Grant No.LP2024005),and the Key Program of the National Natural Science Foundation of China(Grant No.52231013),and the National Natural Science Founda-tion of China(Grant No.12427809),and the National Key R&D Program of China(2022YFC3101901),and the Northwestern Pol-ytechnical University Fund(D5000240072).

10.1016/j.dt.2025.11.003

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