This paper investigates the use of artificial neural networks (ANNs) for modeling and control of the lithographic offset color printing process. The color controller consists of two ANNs; the controller network, which learns an inverse model of the process, takes a set of desired colors as input and generates a set of ink key settings, while the model network learns a forward model of the process through which the controller network can be adapted by using the error backpropagation method. We use three-layer networks with “local” connections between neurons of adjacent layers for the process model as well as for the controller; the architectures address the spatial relationship of multiple inking zones and consider the crosswise ink flow effects existing in the printing process.

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