Name
Abstract | ||
|---|---|---|
We study the dynamics of a simple bistable system driven by multiplicative correlated noise. Such system mimics the dynamics of classical attractor neural networks with an additional source of noise associated, for instance, with the stochasticity of synaptic transmission. We found that the multiplicative noise, which performs as a fluctuating barrier separating the stable solutions, strongly influences the behaviour of the system, giving rise to complex time series and scale-free distributions for the escape times of the system. This finding may be of interest to understand nonlinear phenomena observed in real neural systems and to design bio-inspired artificial neural networks with convenient complex characteristics. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/978-3-642-02478-8_3 | IWANN (1) |
Keywords | Field | DocType |
classical attractor neural network,multiplicative noise,switching dynamics,multiplicative correlated noise,escape time,multiplicative colored noise,convenient complex characteristic,real neural system,neural systems,artificial neural network,simple bistable system,complex time series,additional source,col,scale free,colored noise,synaptic transmission,time series | Statistical physics,Attractor,Bistability,Colors of noise,Nonlinear phenomena,Multiplicative function,Computer science,Simulation,Neural system,Artificial intelligence,Artificial neural network,Multiplicative noise | Conference |
Volume | ISSN | Citations |
5517 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 5 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jorge F. Mejías | 1 | 38 | 5.30 |
| J J Torres | 2 | 20 | 3.24 |
| Samuel Johnson | 3 | 4 | 1.23 |
| Hilbert J. Kappen | 4 | 834 | 103.74 |