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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)(5)
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scopus(8)
Constructive neural networks to pbkp_redict breast cancer outcome by using gene expression profiles
Conference ObjectAbstract: Gene expression profiling strategies have attracted considerable interest from biologist due to thePalabras claves:artificial neural networks, Breast Cancer, Constructive Neural Networks, Gene expression profiles, Pbkp_redictive modellingAutores:Franco L., Jerez-Aragonés J.M., José Luis Subirats, Urda D.Fuentes:scopusApplication of genetic algorithms and constructive neural networks for the analysis of microarray cancer data
ArticleAbstract: Background: Extracting relevant information from microarray data is a very complex task due to the cPalabras claves:Constructive Neural Networks, feature selection, Genetic Algorithms, MicroarrayAutores:Franco L., Jerez-Aragonés J.M., José Luis Subirats, Luque-Baena R.M., Urda D.Fuentes:scopusExtension of the generalization complexity measure to real valued input data sets
Conference ObjectAbstract: This paper studies the extension of the Generalization Complexity (GC) measure to real valued inputPalabras claves:Architecture size, CAIM, Discretization algorithms, neural network, Real-valued functionAutores:Franco L., Gómez I., Jerez-Aragonés J.M., José Luis SubiratsFuentes:scopusFPGA Implementation of Neurocomputational Models: Comparison Between Standard Back-Propagation and C-Mantec Constructive Algorithm
ArticleAbstract: Recent advances in FPGA technology have permitted the implementation of neurocomputational models, mPalabras claves:Constructive Neural Networks, Fpga, Hardware implementationAutores:Francisco Ortega-Zamorano, Franco L., Jerez-Aragonés J.M., Juárez G.E.Fuentes:scopusFPGA implementation comparison between C-mantec and back-propagation neural network algorithms
Conference ObjectAbstract: Recent advances in FPGA technology have permitted the implementation of neurocomputational models, mPalabras claves:Constructive Neural Networks, Fpga, Hardware implementationAutores:Francisco Ortega-Zamorano, Franco L., Jerez-Aragonés J.M., Juárez G.E.Fuentes:scopusNeural network architecture selection: Size depends on function complexity
Conference ObjectAbstract: The relationship between generalization ability, neural network size and function complexity have bePalabras claves:Autores:Franco L., Gómez I., Jerez-Aragonés J.M., José Luis SubiratsFuentes:scopusHybrid (generalization-correlation) method for feature selection in high dimensional DNA microarray pbkp_rediction problems
Conference ObjectAbstract: Microarray data analysis is attracting increasing attention in computer science because of the manyPalabras claves:Constructive Neural Networks, Data Mining, DNA Microarray, feature selectionAutores:Couce Y., Franco L., Jerez-Aragonés J.M., José Luis Subirats, Urda D.Fuentes:scopusLayer multiplexing FPGA implementation for deep back-propagation learning
ArticleAbstract: Training of large scale neural networks, like those used nowadays in Deep Learning schemes, requiresPalabras claves:Deep Neural Networks, Fpga, Hardware implementation, Layer multiplexing, Supervised learningAutores:Francisco Ortega-Zamorano, Franco L., Gómez I., Jerez-Aragonés J.M.Fuentes:scopus