Electromagnetic currents in a relativistic nuclear model

Adagideli, İnanç


Electromagnetic Target Classification using time frequency analysis and neural networks
Sayan, Gönül; Leblebicioğlu, Mehmet Kemal (Wiley, 1999-04-01)
This paper demonstrates the feasibility and advantages of using a self-organizing map (SOM)-type neural network classifier for electromagnetic target recognition. The classifier is supported by a novel feature extraction unit in which the Wigner distribution (WD), a time-frequency representation, is utilized for the extraction of natural-resonance-related energy feature vectors from scattered fields. The proposed target classification technique is tested for a set of canonical targets, displaying an excelle...
Alıyev, Tahmasıb (1986-10-01)
Radiation effects in semiconductor devices
Hanlıoğlu, Gültekin; Özsan, F.Esen; Department of Nuclear Engineering (1989)
Electromagnetic target classification by using time frequency analysis and neural networks
İnce, Türker; Sayan, Gönül Turhan; Leblebicioğlu, Kemal; Department of Electrical and Electronics Engineering (1996)
Electromagnetic target recognition with the fused MUSIC spectrum matrix method: Applications and performance analysis for incomplete frequency data
Secmen, Mustafa; Ekmekci, Evren; Sayan, Gönül (2007-01-01)
The aim of this paper is to apply an electromagnetic target recognition method, which is based on the use of fused MUSIC spectrum matrices, to the case of incomplete frequency domain data. The aforementioned method was suggested recently and succesfully applied to both canonical and complicated targets in the presence of complete frequency domain data [1]. However, most of the real world applications involve the use of severely incomplete frequency data, especially missing low frequency information. In this...
Citation Formats
İ. Adagideli, “Electromagnetic currents in a relativistic nuclear model,” Middle East Technical University, 1995.