A neural-like network approach to residue-to-decimal conversion

In this paper, a neural-like network for computation of residue-to-decimal conversion (RDC), based on a residue reduction operation neural network we proposed, is presented. It is shown both analytically and by simulation that this RDC network is guaranteed to settle into the correct value of RDC within RC time constants, and this network is applicable for variable moduli only by alteration of its operation voltages without requiring parameters of multiplication inverses. In addition, the operation procedure of this RDC network is similar to that of human´s solving RDC problems