Classification of Underwater Echo Based on Fractal Theory and Learning Vector Quantization Neural Network

Pu Hua Tang; Mu Rong Zhou; Ying Yong Bu

doi:10.4028/www.scientific.net/AMM.148-149.1365

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 148-149Classification of Underwater Echo Based on Fractal...

Classification of Underwater Echo Based on Fractal Theory and Learning Vector Quantization Neural Network

Abstract:

A classification method for underwater echo is introduced, which based on fractal theory and learning vector quantization (LVQ) neural network. The fractal dimension was extracted from the underwater echo by continuous wavelet transform. Combining with accumulative energy as input of a LVQ neural network, neural network was used to classify four kinds of underwater echo. The experimental results showed this method is effective and reliable.

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Periodical:

Applied Mechanics and Materials (Volumes 148-149)

Pages:

1365-1369

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.148-149.1365

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Online since:

December 2011

Authors:

Pu Hua Tang, Mu Rong Zhou, Ying Yong Bu

Keywords:

Classify, Continuous Wavelet Transform, Fractal, Learning Vector Quantization (LVQ) Neural Network

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