An integrated Boolean neural network for pattern classification

doi:10.1016/0167-8655(94)90009-4

Pattern Recognition Letters

Volume 15, Issue 8, August 1994, Pages 807-813

https://doi.org/10.1016/0167-8655(94)90009-4 Get rights and content

Abstract

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.

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View full text

An integrated Boolean neural network for pattern classification

Abstract

Internat. J. Man-Machine Studies

Pattern Recognition Lett.

Pattern Recognition Lett.

Wisard: a radical step forward in image recognition

Sensor Review

Improved recognition capabilities for goal seeking neuron

Electronics Lett.

SOFT — a Boolean self organising feature extractor

A lazy learning approach to the training of GSN neural networks

Classifying images using goal seeking neural network architectures

A progressive learning algorithm for GSN feedforward neural architectures