Stochastic resonance as an emergent property of neural networks

2013 ◽  
Author(s):  
M. A. Lopes ◽  
A. V. Goltsev ◽  
K.-E. Lee ◽  
J. F. F. Mendes
Keyword(s):  
Neural Networks ◽  
Stochastic Resonance ◽  
Emergent Property

Localist representations are a desirable emergent property of neurologically plausible neural networks

2000 ◽  
Vol 23 (4) ◽  
pp. 485-486
Author(s):  
Colin Martindale
Keyword(s):  
Neural Networks ◽  
Great Difficulty ◽  
Emergent Property ◽  
Connectionist Models ◽  
Distributed Representations ◽  
Target Article ◽  
Missing Fundamental ◽  
Valuable Service ◽  
Better Than

Page has done connectionist researchers a valuable service in this target article. He points out that connectionist models using localized representations often work as well or better than models using distributed representations. I point out that models using distributed representations are difficult to understand and often lack parsimony and plausibility. In conclusion, I give an example – the case of the missing fundamental in music – that can easily be explained by a model using localist representations but can be explained only with great difficulty and implausibility by a model using distributed representations.

Stochastic resonance in Hopfield neural networks for transmitting binary signals

2020 ◽  
Vol 384 (6) ◽  
pp. 126143 ◽  
Author(s):  
Lingling Duan ◽  
Fabing Duan ◽  
François Chapeau-Blondeau ◽  
Derek Abbott
Keyword(s):  
Neural Networks ◽  
Stochastic Resonance ◽  
Hopfield Neural Networks
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