Feature Extraction of Structures in Sea Water Using Self-Organizing Maps and Electromagnetic Waves

Feature Extraction of Structures in Sea Water Using Self-Organizing Maps and Electromagnetic Waves

ABSTRACT The use of Self-Organizing Map (SOM) algorithm for feature extraction and dimensionality reduction applied to underwater object detection with Low Frequency Electromagnetic Waves is presented. Computer simulation is used to generate a direct model for the study region, and a Self Organizing...

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Bibliographic Details
Main Authors: M.T. SILVA, L.S. BATISTA, F.M.V. DE ALBUQUERQUE
Format: Article
Language:English
Published: Sociedade Brasileira de Matemática Aplicada e Computacional
Series:TEMA
Subjects:
mapas auto-organizáveis
imageamento eletromagnético
redes neurais não-supervisionadas
Online Access:http://www.scielo.br/scielo.php?script=sci_arttext&pid=S2179-84512015000300261&lng=en&tlng=en
Description
Summary:ABSTRACT The use of Self-Organizing Map (SOM) algorithm for feature extraction and dimensionality reduction applied to underwater object detection with Low Frequency Electromagnetic Waves is presented. Computer simulation is used to generate a direct model for the study region, and a Self Organizing Map Algorithm is used to fit the data and return a similar model, with smaller dimensionality and same characteristics. Results show that virtual sensors are created by the SOM algorithm with consistent predictions, filling the resolution gap of the input data. These results are useful for fastening decision making algorithms by reducing the number of inputs to a group of significant data.
ISSN:2179-8451

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