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Perceiving geometric patterns: from spirals to inside-outside relations

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2 Author(s)
Ke Chen ; Dept. of Comput. & Inf. Sci., Ohio State Univ., Columbus, OH, USA ; DeLiang Wang

Since first proposed by Minsky and Papert (1969), the spiral problem is well known in neural networks. It receives much attention as a benchmark for various learning algorithms. Unlike previous work that emphasizes learning, we approach the problem from a different perspective. We point out that the spiral problem is intrinsically connected to the inside-outside problem proposed by Ullman (1984, 1996). We propose a solution to both problems based on oscillatory correlation using a time-delay network. Our simulation results are qualitatively consistent with human performance, and we interpret human limitations in terms of synchrony and time delays. As a special case, our network without time delays can always distinguish these figures regardless of shape, position, size, and orientation

Published in:

IEEE Transactions on Neural Networks  (Volume:12 ,  Issue: 5 )