Observatorio de I+D+i UPM

Descripción
This paper tests a novel improvement in neural network training by implementing Metaplasticity Multilayer Perceptron (MMLP) Neural Networks (NNs), that are based on the biological property of metaplasticity. Artificial Metaplasticity bases its efficiency in giving more relevance to the less frequent patterns and subtracting relevance to the more frequent ones. The statistical distribution of training patterns is used to quantify how frequent a pattern is. We model this interpretation in the NNs training phase. Wisconsin breast cancer database (WBCD) was used to train and test MMLP. Our results were compared to recent research results on the same database, proving to be superior or at least an interesting alternative
Internacional	Si
Nombre congreso	IWANN 09
Tipo de participación	960
Lugar del congreso	Salamanca
Revisores	Si
ISBN o ISSN	978-3-642-02477-1
DOI	10.1007/978-3-642-02478-8
Fecha inicio congreso	10/06/2009
Fecha fin congreso	12/06/2009
Desde la página	174
Hasta la página	179
Título de las actas	Bio-Inspired Systems : Computational and Ambient Intelligence. LCNS 5517

Esta actividad pertenece a memorias de investigación

• Autor: Alexis Enrique Marcano Cedeño (UPM)
• Autor: Aleksandar Jevtic . (UPM)
• Autor: Antonio Jose Alvarez Vellisco (UPM)
• Autor: Diego Andina De la Fuente (UPM)

• Creador: Grupo de Investigación: Grupo de Automatización en Señal y Comunicaciones (GASC)
• Departamento: Ingeniería de Circuitos y Sistemas
• Departamento: Señales, Sistemas y Radiocomunicaciones