Approximation theory of the MLP model in neural networks

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• Approximation theory of the MLP model in neural networks→Multilayer feedforward networks are universal approximatorsLegacy edge — source detail unavailable
• Approximation theory of the MLP model in neural networks→Neural networks for pattern recognitionLegacy edge — source detail unavailable
• Approximation theory of the MLP model in neural networks→Approximation by superpositions of a sigmoidal functionLegacy edge — source detail unavailable
• Approximation theory of the MLP model in neural networks→Neural Networks for Pattern RecognitionLegacy edge — source detail unavailable
• Approximation theory of the MLP model in neural networks→Multilayer feedforward networks are universal approximatorsLegacy edge — source detail unavailable
• Approximation theory of the MLP model in neural networks→An introduction to computing with neural netsLegacy edge — source detail unavailable
• Approximation theory of the MLP model in neural networks→Pattern Recognition and Neural NetworksLegacy edge — source detail unavailable
• Approximation theory of the MLP model in neural networks→Approximation capabilities of multilayer feedforward networksLegacy edge — source detail unavailable
• Approximation theory of the MLP model in neural networks→On the approximate realization of continuous mappings by neural networksLegacy edge — source detail unavailable
• Approximation theory of the MLP model in neural networks→The Handbook of brain theory and neural networksLegacy edge — source detail unavailable
• Approximation theory of the MLP model in neural networks→Neural Information Processing SystemsLegacy edge — source detail unavailable
• Approximation theory of the MLP model in neural networks→A Probabilistic Theory of Pattern RecognitionLegacy edge — source detail unavailable
• Approximation theory of the MLP model in neural networks→Universal approximation bounds for superpositions of a sigmoidal functionLegacy edge — source detail unavailable
• Approximation theory of the MLP model in neural networks→Theory of the backpropagation neural networkLegacy edge — source detail unavailable
• Approximation theory of the MLP model in neural networks→Universal approximation of an unknown mapping and its derivatives using multilayer feedfo…Legacy edge — source detail unavailable
• On the approximate realization of continuous mappings by neural networks→An introduction to computing with neural netsLegacy edge — source detail unavailable
• Approximation capabilities of multilayer feedforward networks→On the approximate realization of continuous mappings by neural networksLegacy edge — source detail unavailable
• Approximation capabilities of multilayer feedforward networks→Universal approximation of an unknown mapping and its derivatives using multilayer feedfo…Legacy edge — source detail unavailable
• Approximation capabilities of multilayer feedforward networks→Approximation by superpositions of a sigmoidal functionLegacy edge — source detail unavailable
• Approximation capabilities of multilayer feedforward networks→Multilayer feedforward networks are universal approximatorsLegacy edge — source detail unavailable
• Approximation capabilities of multilayer feedforward networks→Multilayer feedforward networks are universal approximatorsLegacy edge — source detail unavailable
• Universal approximation of an unknown mapping and its derivatives using multilayer feedfo…→On the approximate realization of continuous mappings by neural networksLegacy edge — source detail unavailable
• Universal approximation of an unknown mapping and its derivatives using multilayer feedfo…→Theory of the backpropagation neural networkLegacy edge — source detail unavailable
• Universal approximation of an unknown mapping and its derivatives using multilayer feedfo…→Multilayer feedforward networks are universal approximatorsLegacy edge — source detail unavailable
• Universal approximation of an unknown mapping and its derivatives using multilayer feedfo…→Multilayer feedforward networks are universal approximatorsLegacy edge — source detail unavailable
• Theory of the backpropagation neural network→Multilayer feedforward networks are universal approximatorsLegacy edge — source detail unavailable
• Approximation by superpositions of a sigmoidal function→On the approximate realization of continuous mappings by neural networksLegacy edge — source detail unavailable
• Approximation by superpositions of a sigmoidal function→An introduction to computing with neural netsLegacy edge — source detail unavailable
• Approximation by superpositions of a sigmoidal function→Multilayer feedforward networks are universal approximatorsLegacy edge — source detail unavailable
• Pattern Recognition and Neural Networks→The Handbook of brain theory and neural networksLegacy edge — source detail unavailable
• Pattern Recognition and Neural Networks→Neural networks for pattern recognitionLegacy edge — source detail unavailable
• Multilayer feedforward networks are universal approximators→Approximation by superpositions of a sigmoidal functionLegacy edge — source detail unavailable
• Multilayer feedforward networks are universal approximators→Multilayer feedforward networks are universal approximatorsLegacy edge — source detail unavailable
• Universal approximation bounds for superpositions of a sigmoidal function→Approximation by superpositions of a sigmoidal functionLegacy edge — source detail unavailable
• Universal approximation bounds for superpositions of a sigmoidal function→Multilayer feedforward networks are universal approximatorsLegacy edge — source detail unavailable