動径基底関数ネットワークにおける肺磁界逆問題の解析

抄録

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