By introducing analogy between electromagnetic field problems and neural network models, new iterative numerical methods are developed for inverse scattering problems. Both recurrent and feedfoward neural network architectures are developed, and the validity of the proposed algorithms is demonstrated by computer simulation for small dielectric cylinders.