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Analogue noise-enhanced learning in neural network circuits

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1 Author(s)
A. F. Murray ; Dept. of Electr. Eng., Edinburgh Univ., UK

Experiments are reported which demonstrate that, whereas digital inaccuracy in neural arithmetic, in the form of bit-length limitation, degrades neural learning, analogue noise enhances it dramatically. The classification task chosen is that of vowel recognition within a multilayer perceptron network, but the findings seem to be perfectly general in the neural context, and have ramifications for all learning processes where weights evolve incrementally, and slowly.

Published in:

Electronics Letters  (Volume:27 ,  Issue: 17 )