Underwater Noise Modeling and Its Application in Noise Classification with Small-Sized Samples
نویسندگان
چکیده
Underwater noise classification is of great significance for identifying ships as well other vehicles. Moreover, it helpful in ensuring a marine habitat-friendly, noise-free ocean environment. But challenge we are facing the small-sized underwater samples. Because influenced by multiple sources, often difficult to determine and label which source or two sources dominant. At present, research solve problem focused on image processing advanced computer technology without starting with generation mechanism modeling. Here, typical model (UNGM) established augment It generating certain kurtosis according spectral statistical characteristics actual filter design. In addition, an developed based UNGM convolutional neural networks (CNN). Then UNGM-CNN-based used classify nine types noise, either 1/3 octave spectrum level (NSL) power density (PSD) input features. The results show that effective improving accuracy. Specifically, increases accuracy 1.59%, from 98.27% 99.86%, 2.44%, 97.45% 99.89%, when NSL PSD features, respectively. Additionally, method appreciably improves macro-precision macro-recall approximately 0.87% 0.83%, respectively, compared CNN-based method. These demonstrate effectiveness
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ژورنال
عنوان ژورنال: Electronics
سال: 2023
ISSN: ['2079-9292']
DOI: https://doi.org/10.3390/electronics12122669