An inverse scattering problem of estimating the reflection coefficient and the surface impedance from two sets of absolute values of the near field with periodic change is investigated. The problem is formulated in terms of a nonlinear simultaneous equations which is derived from the relation between the two sets of absolute values and the field defined by a finite summation of the modal functions by applying the Fourier analysis. The reflection coefficient is estimated by solving the equations by Newton's method through the successive algorithm with the increment of the number of truncation in the summation one after another. Numerical examples are given and the accuracy of the estimation is discussed.

The cause-and-effect relation between plasmon-resonance absorption and surface wave in a sinusoidal metal grating is investigated. By introducing an equivalent impedance model, similar to an equivalent circuit on an electric circuit, which is an impedance boundary value problem on the fictitious surface over the grating, we estimate the surface wave from the eigen field of the model by using the resonance property of the scattered field. Through numerical examples, we illustrate that the absorption in the grating occurs in the condition of exciting the surface wave along the model, and the real part of the surface impedance is negative on about half part of the fictitious surface in the condition.

Presented in this paper is a neural back propagation algorithm for reconstructing two-dimensional CT images from a small number of projection data. The paper extends the work in [1], in which a backpropagation algorithm is applied to the CT image reconstruction problem. The delta rule of the ordinary backpropagation algorithm is modified using a 'secondary' teaching signal and the 'Resilient backpropagation' scheme. Results obtained are presented along with those of two well known conventional methods: MART and EMML method. A quantitative evaluation reveals the effectiveness of the proposed algorithm.