Automatic Tuning of a Retina Model for a Cortical Visual Neuroprosthesis Using a Multi-Objective Optimization Genetic Algorithm
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Título: | Automatic Tuning of a Retina Model for a Cortical Visual Neuroprosthesis Using a Multi-Objective Optimization Genetic Algorithm |
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Autor/es: | Martínez-Álvarez, Antonio | Crespo-Cano, Rubén | Díaz-Tahoces, Ariadna | Cuenca-Asensi, Sergio | Ferrández, José Manuel | Fernández Jover, Eduardo |
Grupo/s de investigación o GITE: | UniCAD: Grupo de investigación en CAD/CAM/CAE de la Universidad de Alicante |
Centro, Departamento o Servicio: | Universidad de Alicante. Departamento de Tecnología Informática y Computación |
Palabras clave: | Retinal modeling | Visual neuroprostheses | Multi-objective optimization | NSGA-II | Evolutionary search |
Área/s de conocimiento: | Arquitectura y Tecnología de Computadores |
Fecha de publicación: | 28-jun-2016 |
Editor: | World Scientific Publishing |
Cita bibliográfica: | International Journal of Neural Systems. 2016, 26(7): 1650021. doi:10.1142/S0129065716500210 |
Resumen: | The retina is a very complex neural structure, which contains many different types of neurons interconnected with great precision, enabling sophisticated conditioning and coding of the visual information before it is passed via the optic nerve to higher visual centers. The encoding of visual information is one of the basic questions in visual and computational neuroscience and is also of seminal importance in the field of visual prostheses. In this framework, it is essential to have artificial retina systems to be able to function in a way as similar as possible to the biological retinas. This paper proposes an automatic evolutionary multi-objective strategy based on the NSGA-II algorithm for tuning retina models. Four metrics were adopted for guiding the algorithm in the search of those parameters that best approximate a synthetic retinal model output with real electrophysiological recordings. Results show that this procedure exhibits a high flexibility when different trade-offs has to be considered during the design of customized neuro prostheses. |
URI: | http://hdl.handle.net/10045/66078 |
ISSN: | 0129-0657 (Print) | 1793-6462 (Online) |
DOI: | 10.1142/S0129065716500210 |
Idioma: | eng |
Tipo: | info:eu-repo/semantics/article |
Derechos: | © World Scientific Publishing Company |
Revisión científica: | si |
Versión del editor: | http://dx.doi.org/10.1142/S0129065716500210 |
Aparece en las colecciones: | INV - UNICAD - Artículos de Revistas |
Archivos en este ítem:
Archivo | Descripción | Tamaño | Formato | |
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2016_Martinez-Alvarez_etal_IntJNeuralSyst_final.pdf | Versión final (acceso restringido) | 4,78 MB | Adobe PDF | Abrir Solicitar una copia |
2016_Martinez-Alvarez_etal_IntJNeuralSyst_revised.pdf | Versión revisada (acceso abierto) | 1,14 MB | Adobe PDF | Abrir Vista previa |
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