Perceiving without Learning: From Spirals to Inside/Outside Relations

As a benchmark task, the spiral problem is well known in neural net(cid: 173) works. Unlike previous work that emphasizes learning, we approach the problem from a generic perspective that does not involve learning. We point out that the spiral problem is intrinsically connected to the in(cid: 173) side/outside problem. A generic solution to both problems is proposed based on oscillatory correlation using a time delay network. Our simu(cid: 173) lation results are qualitatively consistent with human performance, and we interpret human limitations in terms of synchrony and time delays, both biologically plausible. As a special case, our network without time delays can always distinguish these figures regardless of shape, position, size, and orientation.

Authors

• Ke Chen The State Key Laboratory of Blockchain and Data Security, Zhejiang University Hangzhou High-Tech Zone (Binjiang) Institute of Blockchain and Data Security
• Deliang Wang Faculty of Education, The University of Hong Kong

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