Problems of artificial neural networks used for printer color space conversion

Based on an analysis of the corresponding relationship between the input data (RGB) and the measured output data (L^*a^*b^*) of a color printer, it is found that in some color regions, one set of assigned L^*a^*b^* values may correspond to two or more sets of different input RGB values. On the other side, the fact that an established artificial neural network can only produce one (or one set of) definite output in response to any (or any set of) given input implies that neural networks are not suitable, at least when high accuracy is expected, to be used in the cases where it is suppose that one input may correspond to more than one outputs. Thus, it is conclude that the neural network is not suitable to be used as a tool to find out a proper set of RGB for a printer to print out an assigned color (L^*a^*b^*), at least this is case when the accuracy of the said color reproduction is high.