Systolic implementation of higher-order CMAC and its application in colour calibration

Abstract

The primary advantages of a CMAC neural network are fast learning and insensitivity to the order in which training patterns are presented. The authors present an extended direct weight cell address mapping mechanism based on a linear systolic array architecture to realise a higher-order CMAC neural network with digital hardware. This higher-order CMAC implementation has been applied to calibrate and compensate the nonlinearity of chromatic mapping between colour scanning and printing devices in a colour image reproduction environment. A 20 MHz prototyped CMAC chip for colour calibration has been implemented to confirm the proposed design approach. Using this prototype, the authors were able to achieve reproduced colour images with rich and vivid colours which strongly resemble the original.