Unsupervised Electromagnetic Target Classification by Self-organizing Map Type Clustering

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