Mostrando 10 resultados de: 32
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scopus(32)
High precision FPGA implementation of neural network activation functions
Conference ObjectAbstract: The efficient implementation of artificial neural networks in FPGA boards requires tackling severalPalabras claves:Autores:Francisco Ortega-Zamorano, Franco L., Jerez-Aragonés J.M., Juárez G.E., Perez J.O.Fuentes:scopusHybrid (generalization-correlation) method for feature selection in high dimensional DNA microarray prediction 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:scopusEnergy-efficient reprogramming in WSN using constructive neural networks
ArticleAbstract: In this paper, we propose the use of neural network based technologies to carry out the dynamic reprPalabras claves:Constructive Neural Networks, Dynamic reprogramming, Feedforward neural networks, Wireless Sensor NetworksAutores:Aragonés J.M.J., Carmona E.C., Franco L., José Luis Subirats, Torres L.M.L., 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 Hardware Acceleration of Monte Carlo Simulations for the Ising Model
ArticleAbstract: A two-dimensional Ising model with nearest-neighbors ferromagnetic interactions is implemented in aPalabras claves:Hardware implementation, Ising model, LFSR random number generator, Monte Carlo simulationsAutores:Cannas S.A., Francisco Ortega-Zamorano, Franco L., Jerez-Aragonés J.M., Montemurro M.A.Fuentes: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:scopusFPGA implementation of the c-mantec neural network constructive algorithm
ArticleAbstract: Competitive majority network trained by error correction (C-Mantec), a recently proposed constructivPalabras claves:Circuit complexity, constructive neural networks (CoNN), on-chip learning, Threshold networksAutores:Francisco Ortega-Zamorano, Franco L., Jerez-Aragonés J.M.Fuentes:scopusDeep neural network architecture implementation on FPGAs using a layer multiplexing scheme
Conference ObjectAbstract: In recent years predictive models based on Deep Learning strategies have achieved enormous success iPalabras claves:Deep Neural Networks, Fpga, Hardware implementation, Layer multiplexing, Supervised learningAutores:Francisco Ortega-Zamorano, Franco L., Gómez I., Jerez-Aragonés J.M.Fuentes:scopusC-Mantec: A novel constructive neural network algorithm incorporating competition between neurons
ArticleAbstract: C-Mantec is a novel neural network constructive algorithm that combines competition between neuronsPalabras claves:Active learning, Constructive neural network, Feed-forward network, generalization, Incremental learning, OverfittingAutores:Franco L., Jerez-Aragonés J.M., José Luis SubiratsFuentes:scopus