Learning in linear feature-discovery networks

Todd K. Leen

doi:10.1117/12.49799

1 December 1991 Learning in linear feature-discovery networks

Todd K. Leen

Proceedings Volume 1565, Adaptive Signal Processing; (1991) https://doi.org/10.1117/12.49799
Event: San Diego, '91, 1991, San Diego, CA, United States

Abstract

We describe the dynamics of learning in unsupervised linear feature-discovery networks that have recurrent lateral connections. Bifurcation theory provides a description of the location of multiple equilibria and limit cycles in the weight-space dynamics.

Citation Download Citation

Todd K. Leen "Learning in linear feature-discovery networks", Proc. SPIE 1565, Adaptive Signal Processing, (1 December 1991); https://doi.org/10.1117/12.49799

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