doi: 10.7763/IJMO.2012.V2.222
Reducing the Active Paths Interference in the Chialvo-Bak “Minibrain” Model
A. Kulakov
,
M. Zwoliński
- University of Southampton, Southampton, UK.
Abstract
We examine a simple biologically-motivated neural network, the version of the Chialvo-Bak “minibrain”, and propose an approach to decrease the negative effect of the active paths interferences in a process of learning new data. For this purpose we use randomly ordered neural network structure with recurrent signal propagation mode. We investigated the network's performance and learning capacity dependence on its nodes' interconnection level. Our simulation study shows that the proposed approach needs on average 40% less number of learning steps for learning the same set of patterns and has higher learning capacity compared to the existing method.
Keywords
- Hebbian learning
- neural network
- pattern recognition
- reinforcement learning
How to Cite
A. Kulakov and M. Zwoliński, "Reducing the Active Paths Interference in the Chialvo-Bak “Minibrain” Model," International Journal of Modeling and Optimization, vol. 2, no. 6, pp. 734-737, 2012. https://doi.org/ 10.7763/IJMO.2012.V2.222
Copyright & License
Copyright © 2012 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).