Add to ORKGAn attractor neural network on the small-world topology is studied. A learning pattern is presented to the network, then a stimulus carrying local information is applied to the neurons and the retrieval of block-like structure is investigated. A synaptic noise decreases the memory capability. The change of stability from local to global attractors is shown to depend on the long-range character of the network connectivity.This work was supported by TIN 2004-04363-CO03-03, TIN 2007-65989 and CAM S-SEM-0255-2006
Original article can be found at: http://www.informaworld.com/smpp/title~content=t713411269--Copyrig...
Memory is a fundamental part of computational systems like the human brain. Theoretical models ident...
Despite significant progress in our understanding of the brain at both microscopic and macroscopic s...
An attractor neural network on the small-world topology is studied. A learning pattern is presented ...
The model of neural networks on the small-world topology, with metric (local and random connectivit...
The retrieval abilities of spatially uniform attractor networks can be measured by the global overla...
The model of neural networks on the small-world topology, with metric (local and random connectivity...
Tesis doctoral inédita. Universidad Autónoma de Madrid, Escuela Politécnica Superior, departamento d...
scopus:eid=2-s2.0-78751676189 We study the storage of phase-coded patterns as stable dynamical attra...
The original publication is available at www.springerlink.com . Copyright SpringerIn this paper we r...
Copyright 2007 American Institute of Physics. This article may be downloaded for personal use only. ...
<p>The network is comprised of N = 70×70 = 4900 neurons, each connected to <i>C</i> = 0.05<i>N</i> o...
The final publication is available at Springer via http://dx.doi.org/10.1007/11840817_25Proceedings ...
Copyright IEEE. Personal use of this material is permitted. However, permission to reprint/republish...
A fundamental problem in neuroscience is understanding how working memory-the ability to store infor...
Original article can be found at: http://www.informaworld.com/smpp/title~content=t713411269--Copyrig...
Memory is a fundamental part of computational systems like the human brain. Theoretical models ident...
Despite significant progress in our understanding of the brain at both microscopic and macroscopic s...
An attractor neural network on the small-world topology is studied. A learning pattern is presented ...
The model of neural networks on the small-world topology, with metric (local and random connectivit...
The retrieval abilities of spatially uniform attractor networks can be measured by the global overla...
The model of neural networks on the small-world topology, with metric (local and random connectivity...
Tesis doctoral inédita. Universidad Autónoma de Madrid, Escuela Politécnica Superior, departamento d...
scopus:eid=2-s2.0-78751676189 We study the storage of phase-coded patterns as stable dynamical attra...
The original publication is available at www.springerlink.com . Copyright SpringerIn this paper we r...
Copyright 2007 American Institute of Physics. This article may be downloaded for personal use only. ...
<p>The network is comprised of N = 70×70 = 4900 neurons, each connected to <i>C</i> = 0.05<i>N</i> o...
The final publication is available at Springer via http://dx.doi.org/10.1007/11840817_25Proceedings ...
Copyright IEEE. Personal use of this material is permitted. However, permission to reprint/republish...
A fundamental problem in neuroscience is understanding how working memory-the ability to store infor...
Original article can be found at: http://www.informaworld.com/smpp/title~content=t713411269--Copyrig...
Memory is a fundamental part of computational systems like the human brain. Theoretical models ident...
Despite significant progress in our understanding of the brain at both microscopic and macroscopic s...