HYDROACOUSTICS
ANNUAL JOURNAL
START NEW VOL 20 SEARCH STATISTICS PAS - GDANSK DIVISION

Incremental neuro-fuzzy classifiers of seabed using wavelet decomposition

pp. 19-24, vol. 3, 2000

T. V. Dung
Technical University of Gdańsk, Department of Remote Sensing and Monitoring Systems, Gdańsk, Poland

Andrzej Stepnowski
Technical University of Gdańsk, Department of Remote Sensing and Monitoring Systems, Gdańsk, Poland

Marek Moszyński
Technical University of Gdańsk, Department of Remote Sensing and Monitoring Systems, Gdańsk, Poland

Key words:

Abstract: The neuro-fuzzy classifier of seabed type from acoustic echoes was investigated in the context of possible reducing the number of input parameters. The incremental architecture of fuzzy neural network classifier (IFNN) was used in the experiment, utilising dual-frequency echo collection. In particular, the wavelet decomposition of these bottom echoes was used to generate input parameters of IFNN. The Principal Component Analysis (PCA) was subsequently applied for redundant parameters reduction.

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© Polish Acoustical Society - Gdansk Department, Polish Academy of Sciences. This work is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported. (CC BY-NC-SA 3.0)