An integrated Boolean neural network for pattern classification

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This paper describes an integrated approach to pattern classification where a self-organising Boolean neural network architecture is used as a front-end processor to a feedforward neural architecture based on goal-seeking principles (the GSN architecture). The performance of the integrated architecture is illustrated by considering its application to a character recognition problem.