Influence of topology on neural networks based on the recognition of neural signatures
We study the emerging collective dynamics of a neural network model that emits and recognizes neural signatures with different network topologies in order to assess the capacity of a neural network to implement a signaturebased information processing strategy. Complex collective dynamics emerge in t...
| Autores: | , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2013 |
| País: | España |
| Institución: | Universidad Autónoma de Madrid |
| Repositorio: | Biblos-e Archivo. Repositorio Institucional de la UAM |
| Idioma: | inglés |
| OAI Identifier: | oai:repositorio.uam.es:10486/666412 |
| Acceso en línea: | http://hdl.handle.net/10486/666412 https://dx.doi.org/10.1016/j.neucom.2004.01.048 |
| Access Level: | acceso abierto |
| Palabra clave: | Neuron signature Local contextualization Local discrimination Processing based on signal identification Multicoding Self-organizing neural network MSC 2000: 92C20, 92C55, 94C15, 37M10, 93A30 Informática |
| Sumario: | We study the emerging collective dynamics of a neural network model that emits and recognizes neural signatures with different network topologies in order to assess the capacity of a neural network to implement a signaturebased information processing strategy. Complex collective dynamics emerge in the proposed model in the presence of stimuli, i.e. specific incoming signatures. Results presented in this paper point out that neural information processing based on the recognition of signal sources is a plausible, flexible and powerful strategy for neural coding. |
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