Abstract
Invariant pattern recognition will be a problem facing neural networks for some time, and the challenge is to overcome the limitation of Hamming distance generalization. Four representative architectures that are able to generalize are reviewed. The architectures are the backpropagation network, the ART architecture, the dynamic link architecture, and associate memories. Image representation, segmentation, and invariance are discussed.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
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