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A new constructive approach for creating all linearly separable (threshold) functions
Conference ObjectAbstract: A new constructive approach for creating all linearly separable functions is introduced. Balanced anPalabras claves:Autores:Anthony M., Franco L., Jerez-Aragonés J.M., José Luis SubiratsFuentes:scopusCommittee c-mantec: A probabilistic constructive neural network
Conference ObjectAbstract: C-Mantec is a recently introduced constructive algorithm that generates compact neural architecturesPalabras claves:Committee networks, Constructive Neural Networks, Supervised classificationAutores:Francisco Ortega-Zamorano, Franco L., Jerez-Aragonés J.M., José Luis Subirats, Luque-Baena R.M., Urda D.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:scopusActive learning using a constructive neural network algorithm
Conference ObjectAbstract: Constructive neural network algorithms suffer severely from overfitting noisy datasets as, in generaPalabras claves:Autores:Franco L., Jerez-Aragonés J.M., José Luis Subirats, Molina I.Fuentes:scopusEfficient Implementation of the Backpropagation Algorithm in FPGAs and Microcontrollers
ArticleAbstract: The well-known backpropagation learning algorithm is implemented in a field-programmable gate arrayPalabras claves:Embedded Systems, field-programmable gate array (FPGA), Hardware implementation, Microcontrollers, Supervised learningAutores:Francisco Ortega-Zamorano, Franco L., Jerez-Aragonés J.M., Luque-Baena R.M., Urda D.Fuentes:scopusHigh 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: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 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:scopusImplementation of the C-mantec neural network constructive algorithm in an arduino uno microcontroller
Conference ObjectAbstract: A recently proposed constructive neural network algorithm, named C-Mantec, is fully implemented in aPalabras claves:Arduino, Constructive Neural Networks, microcontrollerAutores:Francisco Ortega-Zamorano, Franco L., Jerez-Aragonés J.M., José Luis Subirats, Molina I.Fuentes:scopusImproving learning and generalization capabilities of the C-Mantec constructive neural network algorithm
ArticleAbstract: C-Mantec neural network constructive algorithm Ortega (C-Mantec neural network algorithm implementatPalabras claves:C-Mantec, Constructive neural network, Feed-forward network, Learning and generalization properties, Loading problem, Support Vector MachineAutores:Francisco Ortega-Zamorano, Franco L., Gómez I., Jerez-Aragonés J.M., Mesa H.Fuentes:scopus