An inverse-problem analysis of magnetopneumography with RBFN

In this paper, we analyze the inverse problem of magnetopneumography (the magnetic field pattern produced from the lung) by radial basis function networks (RBFN) with smoothing ability. We show that radial basis function is naturally derived by calculation of the magnetic fields and RBFN composes of elements with such output function that is useful for the inverse problem of magnetopneumography.