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New iterative inverse scattering algorithms based on neural networks

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5 Author(s)
Hyuek-Jae Lee ; GoldStar Central Res. Lab., Seoul, South Korea ; Chang-Hoi Ahn ; Cheon-Seok Park ; Bong-Sik Jeong
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By introducing analogy between electromagnetic field problems and neural network models, new iterative numerical methods are developed for inverse scattering problems. Both recurrent and feedforward neural network architectures are developed, and the validity of the proposed algorithms is demonstrated by computer simulation for small dielectric cylinders

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Magnetics, IEEE Transactions on  (Volume:30 ,  Issue: 5 )