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

Authors

  • Murilo Teixeira Silva Instituto Federal de Educação, Ciência e Tecnologia da Bahia - IFBA
  • Lurimar Smera Batista Instituto Federal de Educação, Ciência e Tecnologia da Bahia - IFBA
  • Frederico Medeiros Vasconcelos de Albuquerque Marinha do Brasil

DOI:

https://doi.org/10.5540/tema.2015.016.03.0261

Keywords:

Neural networks, Self organizing maps, Electromagnetism, Underwater environment

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.

Author Biography

Frederico Medeiros Vasconcelos de Albuquerque, Marinha do Brasil

Grupo de Avaliação e Adestramento em Guerra de Minas (GAAGueM)

References

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Published

2016-01-28

How to Cite

Silva, M. T., Batista, L. S., & de Albuquerque, F. M. V. (2016). Feature Extraction of Structures in Sea Water Using Self-Organizing Maps and Electromagnetic Waves. Trends in Computational and Applied Mathematics, 16(3), 261. https://doi.org/10.5540/tema.2015.016.03.0261

Issue

Vol. 16 No. 3 (2015)

Section

Original Article

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