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Comparison of scattered signal waveform recovery techniques under low SNR for target identification 

Selver, M.A.; Secmen, M.; Zoral, E.Y. (2017 11th European Conference on Antennas and Propagation, EUCAP 2017, 2017)
Target identification from scattered electromagnetic waves is a difficult problem especially at low SNR levels, which prevents extraction of distinguishable information. When a scattered signal is corrupted by noise, it ...
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The effects of geometric scattered signal waveform modeling on target identification performance 

Selver, M.A.; Secmen, M.; Zoral, E.Y. (2017 11th European Conference on Antennas and Propagation, EUCAP 2017, 2017)
Target identification from scattered signals using time domain techniques depend significantly on the waveform. Recently, a novel feature set is proposed which encounter structural properties of the waveform and collects ...
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Hierarchical Reconstruction and Structural Waveform Analysis for Target Classification 

Selver, M.A.; Taygur, M.M.; Secmen, M.; Zoral, E.Y. (IEEE Transactions on Antennas and Propagation, 2016)
Classification of objects from scattered electromagnetic waves is a difficult problem, as it heavily depends on aspect angle. To minimize this dependency, distinguishable features can be used. In this paper, we propose a ...
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Application of dielectric resonator based metamaterial in waveguide coupler 

Kalender, G.; Zoral, E.Y.; Secmen, M. (2016 10th European Conference on Antennas and Propagation, EuCAP 2016, 2016)
In this study, an implementation of the metamaterial structure is used in a waveguide directional coupler. For this purpose, a four-hole waveguide directional coupler in X-band is designed. Then, the block of dielectric-resonator ...
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Real time classification of targets using waveforms in resonance scattering region 

Selver, M.A.; Zoral, E.Y.; Secmen, M. (European Microwave Week 2015: "Freedom Through Microwaves", EuMW 2015 - Conference Proceedings; 2015 45th European Microwave Conference Proceedings, EuMC, 2015)
The classification of similar shaped objects from scattered electromagnetic waves is a difficult problem, as it heavily depends on the aspect angle. The reduction of the adverse effects of the aspect angle is possible by ...
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Effective permittivity and permeability of dielectric resonator arrays in rectangular waveguide for metamaterial applications 

Kalender, G.; Secmen, M.; Zoral, E.Y. (IEEE Antennas and Propagation Society, AP-S International Symposium (Digest), 2015)
The study describes the effective permittivity and permeability calculation of dielectric resonator arrays embedded in a WR90 rectangular waveguide structure. The scattering parameters are extracted and verified with ...
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Real time classification of targets using waveforms in resonance scattering region 

Selver, M.A.; Zoral, E.Y.; Secmen, M. (2015 European Radar Conference, EuRAD 2015 - Proceedings, 2015)
The classification of similar shaped objects from scattered electromagnetic waves is a difficult problem, as it heavily depends on the aspect angle. The reduction of the adverse effects of the aspect angle is possible by ...
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Metamaterial characteristics of dielectric resonator arrays in rectangular waveguide and free space [Dielektrik Rezonatör Dizisinin Dikdörtgen Dalga Kilavuzu ve Serbest Uzaydaki Metamalzeme Karakteristiʇi] 

Kalender, G.; Secmen, M.; Zoral, E.Y. (2015 23rd Signal Processing and Communications Applications Conference, SIU 2015 - Proceedings, 2015)
The study demonstrates the metamaterial characteristics of the arrays containing dielectric resonators by evaluating the permittivity and permeability coefficients of the array structures in rectangular waveguide and free ...
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Transferring Synthetic Elementary Learning Tasks to Classification of Complex Targets 

Selver, M.A.; Toprak, T.; Secmen, M.; Zoral, E.Y. (IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2019)
Deep learning has a promising impact on target classification performance at the expense of huge training data requirements. Therefore, the use of simulated data is inevitable for convergence of deep models (DMs). However, ...
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Utilizing Resonant Scattering Signal Characteristics of Magnetic Spheres via Deep Learning for Improved Target Classification 

Selver, M.A.; Toprak, T.; Secmen, M.; Zoral, E.Y. (IEEE, 2019)
Object classification using LAte-time Resonant Scattering Electromagnetic Signals (LARSESs) is a significant problem found in different areas of application. Due to their special properties, spherical objects play an ...
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Secmen, M. (22)
Zoral, E.Y. (22)
Selver, M.A. (16)Kalender, G. (6)Toprak, T. (4)Taygur, M.M. (2)Date Issued2015 (8)2016 (6)2017 (4)2019 (4)Has File(s)No (22)

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