1 July 1992 Boltzmann distributions and neural networks: models of unbalanced interpretations of reversible patterns
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Abstract
The paper describes a neural network model of the perceptual alternation of ambiguous patterns with unbalanced alternative interpretations. The network is made up by binary `neurons' fully and symmetrically interconnected. An energy function can be introduced; therefore, the analogy between the presented model and magnetic systems is exploited to study the statistical properties of the system. On the basis of considerations related to statistical mechanics, the probabilities of `occupation' of the two phase-space regions, associated with the two interpretations of an ambiguous figure, can be determined and analyzed.zed
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Francesco Masulli, Francesco Masulli, Massimo Riani, Massimo Riani, Enrico Simonotto, Enrico Simonotto, Fabrizio Vannucci, Fabrizio Vannucci, } "Boltzmann distributions and neural networks: models of unbalanced interpretations of reversible patterns", Proc. SPIE 1710, Science of Artificial Neural Networks, (1 July 1992); doi: 10.1117/12.140093; https://doi.org/10.1117/12.140093
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