Failure of outer-product learning to perform higher-order mapping

Details Failure of outer-product learning to perform higher-order mapping Failure of outer-product learning to perform higher-order mapping

Nov 1991

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1991spie.1541..187k&link_type=abstract

Proc. SPIE Vol. 1541, p. 187-198, Infrared Sensors: Detectors, Electronics, and Signal Processing, T. S. Jayadev; Ed.

Computer Science

Learning

Scientific paper

Outer-product learning (also referred to as Hebbian learning) has been used as a very simple training algorithm for neural networks. Outer-product learning also has been proposed as a method for training a network with higher-order interconnections. It is shown in this paper that outer-product learning is inappropriate for higher-order networks because it does not have the ability to perform a non-monotonic mapping.

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