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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/3482

Title: Learning strategy for the binary perceptron
Authors: Reimers, L
BOUTEN, Marcus
VAN ROMPAEY, Bart
Issue Date: 1996
Publisher: IOP PUBLISHING LTD
Citation: JOURNAL OF PHYSICS A-MATHEMATICAL AND GENERAL, 29(19). p. 6247-6252
Abstract: Pursuing the work of Penney and Sherrington, we determine the optimal continuous-weight perceptron which, on clipping, correctly predicts the largest number of weights for the binary perceptron with maximum stability. We calculate the fraction of correctly predicted binary weights when only the continuous weights stronger than a certain threshold are clipped. We finally carry out simulations for a perceptron with 50 weights to test the practicability of different learning strategies.
Notes: Reimers, L, LIMBURGS UNIV CTR,UNIV CAMPUS,B-3590 DIEPENBEEK,BELGIUM.
URI: http://hdl.handle.net/1942/3482
DOI: 10.1088/0305-4470/29/19/010
ISI #: A1996VL96000010
ISSN: 0305-4470
Type: Journal Contribution
Appears in Collections: Research publications

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