scholarly journals Capacity bounds and stochastic resonance for binary input binary output channels

Author(s):  
Ira S. Moskowitz ◽  
Paul Cotae ◽  
Pedro N. Safier ◽  
Daniel L. Kang
1995 ◽  
Vol 06 (03) ◽  
pp. 225-231 ◽  
Author(s):  
MARCELO BLATT ◽  
EYTAN DOMANY ◽  
IDO KANTER

We consider two-layered perceptrons consisting of N binary input units, K binary hidden units and one binary output unit, in the limit N≫K≥1. We prove that the weights of a regular irreducible network are uniquely determined by its input-output map up to some obvious global symmetries. A network is regular if its K weight vectors from the input layer to the K hidden units are linearly independent. A (single layered) perceptron is said to be irreducible if its output depends on every one of its input units; and a two-layered perceptron is irreducible if the K+1 perceptrons that constitute such network are irreducible. By global symmetries we mean, for instance, permuting the labels of the hidden units. Hence, two irreducible regular two-layered perceptrons that implement the same Boolean function must have the same number of hidden units, and must be composed of equivalent perceptrons.


2012 ◽  
Vol 60 (2) ◽  
pp. 364-374 ◽  
Author(s):  
Miguel Griot ◽  
Andres I. Vila Casado ◽  
Wen-Yen Weng ◽  
Herwin Chan ◽  
Jiadong Wang ◽  
...  

2003 ◽  
Vol 03 (02) ◽  
pp. L195-L204 ◽  
Author(s):  
JAN A. FREUND ◽  
SYLVAIN BARBAY ◽  
STEFANO LEPRI ◽  
ALESSANDRO ZAVATTA ◽  
GIOVANNI GIACOMELLI

The beneficial role fluctuations can play in the process of phase synchronization is analyzed in terms of a model with binary input and output signals. Special attention is paid to the relation between noise-induced phase synchronization and the well-known phenomenon of stochastic resonance. Analytic predictions are compared with experimental data from a vertical cavity surface emitting laser. Various measures for aperiodic stochastic resonance, frequency entrainment and stochastic phase synchronization reveal a satisfactory agreement between theory and experiment.


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