Underwater target recognition based on wavelet packet entropy and probabilistic neural network
Abstract
A method for underwater target recognition based on wavelet packet entropy and probability neural network is studied in this paper. Wavelet packet transform (WPT) is a time-frequency analysis tool which is developed from wavelet transform (WT). The low-frequency and high-frequency component of a non-stationary signal can be decomposed by WPT simultaneously. The radiated noise of an underwater target is decomposed by WPT and the entropy of terminal nodes through WPT decomposition was selected as feature vector, and is input into a probability neural network (PNN) for underwater target recognition. Simulation result indicates that selecting the entropy as feature vector has higher recognition accurate ratio.
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The auditory-inspired CNN had a high accuracy (87.2%), outperforming a standard CNN (83.2%), a stack of autoencoders (81.4%), wavelet transform with PCA (74.6%), and a support-vector machine (68.2%).
“The results showed that the proposed auditory-inspired CNN had a high accuracy (87.2%), outperforming a standard CNN (83.2%), a stack of autoencoders [113] (81.4%) and various traditional object recognition algorithms, such as a combination of wavelet transform with PCA [114] (74.6%) and a support-vector machine [115] (68.2%).”
From A Survey of Underwater Acoustic Data Classification Methods Using Deep Learning for Shoreline Surveillance (2022) · cites this paper as [114]
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Domingos, L. C. F., Santos, P. E., Skelton, P. S. M., Brinkworth, R. S. A., & Sammut, K. (2022) · Sensors · doi:10.3390/s22062181 · Cited by 93 · see citing works
“%) and various traditional object recognition algorithms, such as a combination of wavelet transform with PCA [114] (74.6”
MethodInfluential
- Authors
- Shi, M., & Xu, X.
- Affiliations
- Chinese People's Liberation Army (CN)
- Venue
- 2013 IEEE International Conference on Signal Processing, Communication and Computing (ICSPCC 2013)
- Publisher
- IEEE
- Published
- 2013-08
- Pages
- 1-3
- OpenAlex
- W2089977773
- Cited by
- 7
- References
- 0
- Citations by year
- 2023: 1 · 2022: 2 · 2021: 1 · 2018: 1 · 2016: 1 · 2015: 1
- FWCI
- 5.21
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC) (publishedVersion)
- Topics
- Physical Sciences › Earth and Planetary Sciences › Oceanography › Underwater Acoustics Research
- Physical Sciences › Engineering › Ocean Engineering › Underwater Vehicles and Communication Systems
- Physical Sciences › Computer Science › Signal Processing › Music and Audio Processing
- Keywords
- underwater target recognition, wavelet packet entropy, wavelet packet decomposition, probabilistic neural network, underwater radiated noise, feature extraction, non-stationary signals, time-frequency analysis
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