数字海洋与水下攻防2026，Vol.9Issue(1)：74-80,7.DOI:10.19838/j.issn.2096-5753.2026.01.007
轻量化多层感知网络的海洋声纹识别
Marine Acoustic Fingerprint Recognition Using Lightweight Multilayer Perceptron Networks
摘要
Abstract
To enhance the classification efficiency and noise resistance capability of marine acoustic fingerprint signals while reducing the computational cost of traditional deep learning models for resource-constrained underwater devices,a lightweight method for marine acoustic recognition is investigated in this paper.By integrating Wiener filtering with a lightweight multilayer perceptron network,an end-to-end recognition pipeline is constructed.The process begins with extraction of Mel-frequency cepstral coefficient features from the acoustic data.An adaptive noise assessment mechanism is then employed to filter and denoise samples with high noise levels,while a lightweight classification network is utilized to achieve high-performance signal recognition.Experiments are demonstrated with a diverse dataset comprising real marine bio-acoustic data from multiple species.The results demonstrate that the proposed method achieves stable overall classification accuracy and exhibits strong recognition performance across different species and their varying behavioral vocalizations.Furthermore,the approach significantly reduces signal processing time and delivers highly robust recognition capabilities on low-computational-power devices.This provides a feasible technical solution for edge monitoring equipment operating in complex marine environments.关键词
声学信号分类/多层感知网络/Wiener 滤波/轻量化/声学信号识别Key words
acoustic signal classification/multilayer perceptron network/Wiener filtering/lightweight/acoustic signal recognition分类
信息技术与安全科学引用本文复制引用
霍致远,刘佳宜,伍飞云,宋丹..轻量化多层感知网络的海洋声纹识别[J].数字海洋与水下攻防,2026,9(1):74-80,7.基金项目
国家自然科学基金青年项目"海上高维数据的高压缩率有损LDPC信源编码研究"(62501252) （62501252）
福建省自然科学基金面上项目"多域水声通信的通用编码技术研究"(2024J01101) （2024J01101）
福建省教育厅面上项目"泛在水声环境的编码算法优化"(JAT231044). （JAT231044）
