| Autor: |
Abdollah-nia, Mohammad-Farshad, Saeedghalati, Mohammadkarim, Abbassian, Abdolhossein |
| Rok vydání: |
2011 |
| Předmět: |
|
| Druh dokumentu: |
Working Paper |
| DOI: |
10.1088/1742-5468/2012/02/P02018 |
| Popis: |
In statistical mechanics, the Potts model is a model for interacting spins with more than two discrete states. Neural networks which exhibit features of learning and associative memory can also be modeled by a system of Potts spins. A spontaneous behavior of hopping from one discrete attractor state to another (referred to as latching) has been proposed to be associated with higher cognitive functions. Here we propose a model in which both the stochastic dynamics of Potts models and an adaptive potential function are present. A latching dynamics is observed in a limited region of the noise(temperature)-adaptation parameter space. We hence suggest noise as a fundamental factor in such alternations alongside adaptation. From a dynamical systems point of view, the noise-adaptation alternations may be the underlying mechanism for multi-stability in attractor based models. An optimality criterion for realistic models is finally inferred. |
| Databáze: |
arXiv |
| Externí odkaz: |
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