Application of New Type BP Neural Networks for Magnetic Measurement

Magnetic measurement is a typical inverse problem in Biomedical field. In this kind of problem we always need to locate the positions and moments of one or more magnetic dipoles. Although using the traditional methods to solve this kind of inverse problem has all kinds of shortcomings, BPNN (Back Propagation Neural Networks) method can be used to solve this typical inverse problem fast enough for real time measurement. In the traditional BPNN method, gradient descent search method is performed for error propagation. In this paper the authors propose a new algorithm that Newton method is performed for error propagation. For the cost function is highly nonconvex in the magnetic measurement problem, the new kind of BPNN can get convergent results quickly and precisely. A simulation result for this method is also presented.