Unsupervised Electromagnetic Target Classification by Self-organizing Map Type Clustering

Date

2010-07-08

Author

Katilmis, T. T.
Ekmekci, E.
Sayan, Gönül

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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In this study, design of a completely unsupervised electromagnetic target classifier will be described based on the use of Self-Organizing Map (SOM) type artificial neural network training and Wigner distribution (WD) based target feature extraction technique. The suggested classification method will be demonstrated for a target library of four dielectric spheres which have exactly the same size but slightly different permittivity values.

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https://hdl.handle.net/11511/54270

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Department of Electrical and Electronics Engineering, Conference / Seminar

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Citation Formats

T. T. Katilmis, E. Ekmekci, and G. Sayan, “Unsupervised Electromagnetic Target Classification by Self-organizing Map Type Clustering,” 2010, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/54270.